Robust comprehension of natural language instructions by a domestic service robot

We present a method through which domestic service robots can comprehend natural language instructions. For each action type, a variety of natural language expressions can be used, for example, the instruction, ‘Go to the kitchen’ can also be expressed as ‘Move to the kitchen.’ We are of the view that natural language instructions are intuitive and, therefore, constitute one of the most user-friendly robot instruction methods. In this paper, we propose a method that enables robots to comprehend instructions spoken by a human user in his/her natural language. The proposed method combines action-type classification, which is based on a support vector machine, and slot extraction, which is based on conditional random fields, both of which are required in order for a robot to execute an action. Further, by considering the co-occurrence relationship between the action type and the slots along with the speech recognition score, the proposed method can avoid degradation of the robot’s comprehension accuracy in noisy environments, where inaccurate speech recognition can be problematic. We conducted experiments using a Japanese instruction data-set collected using a questionnaire-based survey. Experimental results show that the robot’s comprehension accuracy is higher in a noisy environment using our method than when using a baseline method with only a 1-best speech recognition result.     

Text analytics in industry: Challenges,desiderata and trends

The recent decades have witnessed an unprecedented expansion in the volume of unstructured data in digital textual formats. Companies are now starting to recognize the potential economic value lying untapped in their text data repositories and sources, including external ones, such as social media platforms, and internal ones, such as safety reports and other company-specific document collections. Information extracted from these textual data sources is valuable for a range of enterprise application and for informed decision making. In this article we provide a systematic review of the current state of the art in the application of text analytics in industry. Our review is structured along three dimensions: the application context, the methods and techniques utilized, and the evaluation procedure. Based on the review, we identify the different challenges and constraints that an real-world, industrial environment imposes on text analytics techniques, as opposed to their deployment in more controlled, research environments. In addition, we formulate a set of desiderata that text analytics techniques should satisfy in order to alleviate these challenges and to ensure their successful deployment in industry. Furthermore, we discuss future trends in text analytics and their potential application in industry.     

TrendPerceptor: A property-function based technology intelligence system for identifying technology trends from patents

Technology intelligence systems are vital components for planning of technology development and formulation of technology strategies. Although such systems provide computation supports for technology analysis, much effort and intervention of experts, who may be expensive or unavailable, is required in gathering processes of information for analysis. As a remedy, this paper proposes TrendPerceptor, a system that uses a property-function based approach. The proposed system assists experts (1) to identify trends in invention concepts from patents, and (2) to perform evolution trend analysis of patents for technology forecasting. For this purpose, a module of the system uses grammatical analysis of textual information to automatically extract properties and functions, which show innovation directions in a given technology. Using the identified properties and functions, a module for invention concept analysis based on network analysis and a module for evolution trend analysis based on TRIZ (Russian acronym of the Theory of Inventive Problem Solving) trends are suggested. This paper describes the architecture of a system composed of these three modules, and illustrates two case studies using the system.     

Syntax and semantics of universal programming languages

This paper deals with certain characterizations of the sets of positive integers which when represented as strings on a finite alphabet, form tree adjunct languages, As the context free languages constitute a subfamily of tree adjunct languages, the results carry over to the former as well.     

从学生需求看大学英语语言测试——以漓江学院非英语专业学生为例

本文通过访谈法和问卷调查法来了解漓江学院非英语专业学生对英语学习的需求。该研究旨在探寻学生需求和语言测试之间的关系。通过对收集数据的分析,我们发现学生需求和大学英语语言测试相互影响。     

新现代主义服饰产品的符号体系

从新现代主义设计核心理念视角来界定具有新现代主义风格的服饰,按照结构主义和艺术符号学的观点把新现代主义服饰作为一种符号系统,从指示符号、象征符号、形式美学符号三层次解读了新现代主义服饰产品的语言。     

Defuzzification as a special way of dealing with retranslation

The problem of defuzzification is examined in this paper from a broader perspective as a special way of dealing with the general problem of retranslation. The paper includes an overview of different formulations of the problem of defuzzification, as well as an overview of methods that have been suggested in the literature for dealing with the problem. Our own approach to defuzzification, which is described in the paper in more details, is based on relevant measures of uncertainty-based information. This paper is a companion to our recent paper that addresses the general problem of retranslation in computing with perceptions (Martin and Klir 2006).     

《俄勒冈实验》模式原则实施效果评述

C?亚历山大教授在其出版的《俄勒冈实验》一书中，以俄勒冈大学为实验母体，界定出一种设计方式，以适用任何社区的总体规划，并归纳为6种主要原则。文章从现实角度出发，针对俄勒冈大学规划现状，提取6种原则中的模式原则并选择其中较为重要的几项模式对其论述进行比较研究，并依照现有实施状况进行一般性评价。对俄勒冈大学规划现状的研究将为我国高校下一阶段的校园规划和校园更新建设提供一定参考价值。