KNOWLEDGE-BASED FEATURE DISCOVERY FOR EVALUATION FUNCTIONS

Since Samuel's work on checkers over thirty years ago, much effort has been devoted to learning evaluation functions. However, all such methods are sensitive to the feature set chosen to represent the examples. If the features do not capture aspects of the examples significant for problem solving, the learned evaluation function may be inaccurate or inconsistent. Typically, good feature sets are carefully handcrafted and a great deal of time and effort goes into refining and tuning them. This paper presents an automatic knowledge-based method for generating features for evaluation functions. The feature set is developed iteratively: features are generated, then evaluated, and this information is used to develop new features in turn. Both the contribution of a feature and its computational expense are considered in determining whether and how to develop it further.
This method has been applied to two problem-solving domains: the Othello board game and the domain of telecommunications network management. Empirical results show that the method is able to generate many known features and several novel features and to improve concept accuracy in both domains.     

Children's beliefs about drinking

This paper reports the results of a study in which age (grade level), racial/ethnic, and gender differences in beliefs and perceived norms about drinking were examined in a multi-ethnic urban sample of 4th through 7th grade children. Results showed that older children held beliefs and perceived norms that were more favorable toward drinking than younger children. The major difference between older and younger children lay in their differential estimates of the likelihood of certain consequences occurring and not in their evaluation of these consequences of drinking. Further, older children not only displayed less motivation to comply with their parents and greater motivation to comply with their peers, but they also perceived their parents, as well as their peers, as less disapproving of drinking than did younger children. There were few gender or race/ethnicity differences at these ages in children's beliefs and perceived norms about drinking.     

An ET-Based Two-Phase Method for the Calibration and Application of Distributed Hydrological Models

Water Resources Management - Parameter calibration is a core process for the application of distributed hydrological models, which depends strongly on river runoff records. However, the sparse...     

Demonstration of Sustainable Development of Groundwater through Aquifer Storage and Recovery (ASR)

Water Resources Management - Sustained pumping of groundwater can lead to declining water levels in wellfields and concerns regarding the sustainability of groundwater resources. Aquifer Storage...     

Adding sense to the Internet of Things

The Internet of Things (IoT) concept is being widely presented as the next revolution toward massively distributed information, where any real-world object can automatically participate in the Internet and thus be globally discovered and queried. Despite the consensus on the great potential of the concept and the significant progress in a number of enabling technologies, there is a general lack of an integrated vision on how to realize it. This paper examines the technologies that will be fundamental for realizing the IoT and proposes an architecture that integrates them into a single platform. The architecture introduces the use of the Smart Object framework to encapsulate radio-frequency identification (RFID), sensor technologies, embedded object logic, object ad-hoc networking, and Internet-based information infrastructure. We evaluate the architecture against a number of energy-based performance measures, and also show that it outperforms existing industry standards in metrics such as network throughput, delivery ratio, or routing distance. Finally, we demonstrate the feasibility and flexibility of the architecture by detailing an implementation using Wireless Sensor Networks and Web Services, and describe a prototype for the real-time monitoring of goods flowing through a supply chain.     

Cubical Mass-Spring Model design based on a tensile deformation test and nonlinear material model

Mass-Spring Models (MSMs) are used to simulate the mechanical behavior of deformable bodies such as soft tissues in medical applications. Although they are fast to compute, they lack accuracy and their design remains still a great challenge. The major difficulties in building realistic MSMs lie on the spring stiffness estimation and the topology identification. In this work, the mechanical behavior of MSMs under tensile loads is analyzed before studying the spring stiffness estimation. In particular, the performed qualitative and quantitative analysis of the behavior of cubical MSMs shows that they have a nonlinear response similar to hyperelastic material models. According to this behavior, a new method for spring stiffness estimation valid for linear and nonlinear material models is proposed. This method adjusts the stress-strain and compressibility curves to a given reference behavior. The accuracy of the MSMs designed with this method is tested taking as reference some soft-tissue simulations based on nonlinear Finite Element Method (FEM). The obtained results show that MSMs can be designed to realistically model the behavior of hyperelastic materials such as soft tissues and can become an interesting alternative to other approaches such as nonlinear FEM.     

A qualitative human-centric evaluation of flexibility in middleware implementations

Today middleware is much more powerful, more reliable and faster than it used to be. Nevertheless, for the application developer, the complexity of using middleware platforms has increased accordingly. The volume and variety of application contexts that current middleware technologies have to support require that developers be able to anticipate the widest possible range of execution environments, desired and undesired effects of different programming strategies, handling procedures for runtime errors, and so on. This paper shows how a generic framework designed to evaluate the usability of notations (the Cognitive Dimensions of Notations Framework, or CDN) has been instantiated and used to analyze the cognitive challenges involved in adapting middleware platforms. This human-centric perspective allowed us to achieve novel results compared to existing middleware evaluation research, typically centered around system performance metrics. The focus of our study is on the process of adapting middleware implementations, rather than in the end product of this activity. Our main contributions are twofold. First, we describe a qualitative CDN-based method to analyze the cognitive effort made by programmers while adapting middleware implementations. And second, we show how two platforms designed for flexibility have been compared, suggesting that certain programming language design features might be particularly helpful for developers.     

Extension of belief functions to infinite-valued events

We generalise belief functions to many-valued events which are represented by elements of Lindenbaum algebra of infinite-valued ?ukasiewicz propositional logic. Our approach is based on mass assignments used in the Dempster–Shafer theory of evidence. A generalised belief function is totally monotone and it has Choquet integral representation with respect to a unique belief measure on Boolean events.