Declarative Bias for Specific-to-General ILP Systems

A comparative study is presented of language biases employed in specific-to-general learning systems within the Inductive Logic Programming (ILP) paradigm. More specifically, we focus on the biases employed in three well known systems: CLINT, GOLEM and ITOU, and evaluate both conceptually and empirically their strengths and weaknesses. The evaluation is carried out within the generic framework of the NINA system, in which bias is a parameter. Two different types of biases are considered: syntactic bias, which defines the set of well-formed clauses, and semantic bias, which imposes restrictions on the behaviour of hypotheses or clauses. NINA is also able to shift its bias (within a predefined series of biases), whenever its current bias is insufficient for finding complete and consistent concept definitions. Furthermore, a new formalism for specifying the syntactic bias of inductive logic programming systems is introduced.This paper extends the papers (Adé & Bruynooghe, 1992) and (Rouveirol et al., 1993).     

结构不确定离散车组偏差系统分散鲁棒控制

研究具有结构不确定性的离散车组偏差系统的分散鲁棒控制问题.应用大系统包含原理的约束条件扩展系统的信息重叠结构;兼顾系统的结构不确定性和系统数据传榆时延,将扩展后的模型离散化;采用求解线性矩阵不等式( LMIs)的方法设计出系统在无外界干扰情况下的状态反馈分散鲁棒控制器,以及有外界干扰情况下的H∞次优状态反馈分散鲁棒控制器.仿真结果表明,应用所提出的控制方法控制具有结构不确定性的离散车组偏差系统是有效的.     

电网可靠性评估的PSO-SVR评估模型

城市电网结构复杂,数据量大是电网可靠性评估的难点,导致了传统的电网可靠性评估方法难以有效评估.为提高评估的精度和效率,提出一种基于粒子群支持向量回归法的电网可靠性评估的新方法解决电网可靠性评估的问题,采用供电可靠率作为评估指标,粒子群支持向量回归法能克服传统的人工神经网络可靠性评估方法易陷人局部极值.采用电网可靠性评估特征参数与评估指标,确定评估模型结构,再用粒子群优化算法优化支持向量回归模型参数.仿真结果表明,粒子群支持向量回归法可靠性评估精度高于人工神经网络.证明粒子群支持向量回归的电网可靠性评估方法具有更好的应用价值.     

Evaluation of Text Retrieval Systems

Evaluation is one of the main driving forces in studies and developments related to text retrieval. It is a basic tool for the comparison of efficiencies of alternative approaches. In this paper, the state of the art in the field of evaluation of text retrieval systems is surveyed. Two basic—system-oriented and user-oriented— paradigms, which are commonly accepted in this field, are often considered as incompatible. In this survey, both paradigms are considered in the context of a unique framework based on attributes affecting the innovation distribution and adaptation. A detailed discussion of the evaluation of text retrieval systems is based on the consideration of required components of the evaluation process for an arbitrary system. Methodological problems related to the verification of the results obtained are also discussed.     

两个小额电子支付系统的性能评估

小额电子支付系统具有很强的现实意义。详细介绍了两个比较典型的系统：Paywords,SAS-Coin，并从计算量、通信量和安全性等方面对它们的性能进行了评估和分析。     

RFID引起争论

最近几个月,无线射频识别技术(RFID)在美国引发了激烈争论.     

知识融合中的反馈评估和参数校正的机制

提出了一种在知识融合框架结构中建立根据应用结果进行反馈评估和参数校正的机制.相关的知识资源对象和应用需求描述通过本体论方法被表示为知识空间中的对象节点;根据知识融合的特点建立了知识对象的评价参数体系,提出了基于反馈和参数校正机制的自适应模块;分析了该模块与其他模块之间的层次关系,仿真实验说明了该机制的合理性.     

Evaluation Challenges and Directions for Information-Seeking Support Systems

ISSSs provide an exciting opportunity to extend previous information-seeking and interactive information retrieval evaluation models and create a research community that embraces diverse methods and broader participation.     

嵌入式系统的系统测试和可靠性评估

引入多种嵌入式系统的系统测试方法；根据ISO 9000国际质量标准，提出一种切实可行的可靠性评估方案，并将它们应用于嵌入式产品测试中，测试效果良好。最后，通过两个测试实例说明嵌入式系统的系统测试过程和分析。     

User-Centric Learning and Evaluation of Interactive Segmentation Systems

Many successful applications of computer vision to image or video manipulation are interactive by nature. However, parameters of such systems are often trained neglecting the user. Traditionally, interactive systems have been treated in the same manner as their fully automatic counterparts. Their performance is evaluated by computing the accuracy of their solutions under some fixed set of user interactions. In this paper, we study the problem of evaluating and learning interactive segmentation systems which are extensively used in the real world. The key questions in this context are how to measure (1) the effort associated with a user interaction, and (2) the quality of the segmentation result as perceived by the user. We conduct a user study to analyze user behavior and answer these questions. Using the insights obtained from these experiments, we propose a framework to evaluate and learn interactive segmentation systems which brings the user in the loop. The framework is based on the use of an active robot user??a simulated model of a human user. We show how this approach can be used to evaluate and learn parameters of state-of-the-art interactive segmentation systems. We also show how simulated user models can be integrated into the popular max-margin method for parameter learning and propose an algorithm to solve the resulting optimisation problem.     

Empirical Evaluation of User Models and User-Adapted Systems

Empirical evaluations are needed to determine which users are helped or hindered by user-adapted interaction in user modeling systems. A review of past UMUAI articles reveals insufficient empirical evaluations, but an encouraging upward trend. Rules of thumb for experimental design, useful tests for covariates, and common threats to experimental validity are presented. Reporting standards including effect size and power are proposed.     

Assembled Bias: Beyond Transparent Algorithmic Bias

Minds and Machines - In this paper we make the case for the emergence of novel kind of bias with the use of algorithmic decision-making systems. We argue that the distinctive generative process of...     

Bias and pathology in minimax search

This article presents the results of experiments designed to gain insight into the effect of the minimax algorithm on the error of a heuristic evaluation function. Two types of effect of minimax are considered: (a) evaluation accuracy (Are the minimax backed-up values more accurate than the heuristic values themselves?), and (b) decision accuracy (Are moves played by deeper minimax search better than those by shallower search?). The experiments were performed in the King–Rook–King (KRK) chess endgame and in randomly generated game trees. The results show that, counter-intuitively, evaluation accuracy may decline with search depth, whereas at the same time decision accuracy improves with depth. In the article, this is explained by the fact that minimax in combination with a noisy evaluation function introduces a bias into the backed-up evaluations, which masks the evaluation effectiveness of minimax, but this bias still permits decision accuracy to improve with depth. This observed behaviour of minimax in the KRK endgame is discussed in the light of previous studies of pathology in minimax. It is shown that explaining the behaviour of minimax in an actual chess endgame in terms of previously known results requires special care.     

Bias in ergonomic experiments

In a within-subject experimental design, each person receives a number of conditions in a balanced or random order.. The design produces asymmetrical transfer and range effects. Yet practically all ergonomic recommendations are based upon the results of experiments which use this kind of design. The recommendations need to be checked, using separate groups of people for each experimental condition.     

Bias in computer-assisted surveys

The emergence of new technology has enabled rapid data collection via mechanical interviews. Improved speed of data collection enables researchers to collect a larger volume of data with lower interview cost. Computers allow editing during data collection to prevent errors and they direct respondents to relevant questions. They may also facilitate immediate data tabulation and analysis. In spite of these advantages, a concern for bias introduction arises. The reported study finds that direct computer data collection via keyboard provides data as accurate as personal interviews and self-administered forms but may lower response rates on certain questions. This result implies that computers are valid data collection devices in certain situations     

Calibration and Evaluation for Visuo-haptic Collocation in Haptic Augmented Virtuality Systems

International Journal of Control, Automation and Systems - Haptic augmented virtuality systems can provide users with a highly immersive haptic experience by visuo-haptic collocation of physical...     

The Clipper Chip Controversy

Much has been said about Clipper and Capstone chips (the term Clipper will be used to describe both). Essentially, Clipper is a US government-sponsored tamper-resistant chip that employs a classified algorithm and a key escrow facility that allows law enforcement, with the cooperation of two other parties, to decipher Clipper-encrypted traffic. The stated purpose of the program is to offer telecommunications privacy to individuals, businesses, and government, while protecting the ability of law enforcement to conduct court-authorized wiretapping.

This proposal, taken at face value, raises a number of serious questions. In the attempt to get answers, in May of this year I requested that the National Institute of Standards and Technology (NIST) respond to a list of questions. Their responses are included in this column.