An Empirical Investigation Into Text Input Methods for Interactive Digital Television Applications

Nowadays there is a huge market emerging in the interactive digital TV realm. In this context, we need new and effective methods of user interaction, as the main interaction device is still the classical remote control. Remote controls are especially problematic when it comes to writing text, something needed in most applications. Thus, we have carried out an empirical investigation to find effective methods of text entry with remote controls. We analyze several methods by performing experiments based on a methodology in which a heterogeneous set of real users carries out several sequential tasks in an incremental process. We analyze entry speeds, error rates, learning profiles, and subjective impressions, taking into account the particular characteristics of the users. Our results show, for instance, that Multitap is a good method for simple texts. It is between 12% and 34% faster than the fastest virtual keyboard, depending on the age of the user. Nevertheless, when complex texts need to be written, virtual keyboards present the same or even better writing speeds (QWERTY is 13% faster) and with significant lower error rates (Multitap is 347% worse than QWERTY). We consider that our results are very interesting for researchers, designers of TV applications, and hardware vendors.     

Evaluation of Virtual Keyboards for Interactive Digital Television Applications

The development of the technologies behind Interactive Digital Television (IDTV) services has produced a new type of audience. Traditional viewers now become users as they may play an active role in front of the TV, for example, by choosing a video to be played on demand or by introducing text on an IDTV application. In these services, interactions need to be performed with a remote control, currently the main interaction device, or other devices such as keyboards or mice, which are not very popular in this environment. Nevertheless, although remote controls are essential tools for IDTV services, they are very limited when it comes to writing text. Thus, this study evaluated different alternatives to introduce text on an IDTV application with a remote control. A heterogeneous group of people was selected to write predefined sentences in Spanish in a test environment using three virtual keyboard layouts and the multitap mechanism. Their performance and subjective impressions reveal weaknesses and strengths of the evaluated methods. The article draws important conclusions about the usage of remote controls in IDTV applications, not only for the design of new applications but also for the research of new techniques to introduce text.     

Active Learning for Transductive Support Vector Machines with Applications to Text Classification

This paper presents a novel active learning approach for transductive support vector machines with applications to text classification. The concept of the centroid of the support vectors is proposed so that the selective sampling based on measuring the distance from the unlabeled samples to the centroid is feasible and simple to compute. With additional hypothesis, active learning offers better performance with comparison to regular inductive SVMs and transductive SVMs with random sampling,and it is even competitive to transductive SVMs on all available training data. Experimental results prove that our approach is efficient and easy to implement.     

互动电视业务数据源部署及频点管理和分配方法研究

传统互动电视业务数据源与IPQAM连接方式通常会带来业务数据流较大时延、抖动,以及诸多网络安全问题.为了缓解上述问题,本文提出了一种业务数据源与IPQAM直连部署方法.在此部署方法基础上提出一种频点管理和分配算法.仿真实验表明,该管理、分配方法能够很好地兼容本文提出的业务数据源部署方式和传统业务数据源部署方式,并在限制最大服务拒绝率情况下,可提供较高频点带宽利用率.     

A Generalization of Magic Squares with Applications to Digital Halftoning

A semimagic square of order n is an n×n matrix containing the integers 0,…,n ²−1 arranged in such a way that each row and column add up to the same value. We generalize this notion to that of a zero k×k -discrepancy matrix by replacing the requirement that the sum of each row and each column be the same by that of requiring that the sum of the entries in each k×k square contiguous submatrix be the same. We show that such matrices exist if k and n are both even, and do not if k and n are relatively prime. Further, the existence is also guaranteed whenever n=k ^m , for some integers k,m≥2. We present a space-efficient algorithm for constructing such a matrix. Another class that we call constant-gap matrices arises in this construction. We give a characterization of such matrices. An application to digital halftoning is also mentioned. A preliminary version of this paper appeared in Proceedings of International Symposium on Algorithms and Computation, Hong Kong, December, 2004. Part of the work on the paper has been carried out when B.A. was visiting JAIST. Work of B.A. on this paper was supported in part by NSF ITR Grant CCR-00-81964. Work of T.A. was partially supported by the Ministry of Education, Science, Sports and Culture, Grant-in-Aid for Scientific Research (B).     

基于GPU光线投射的多平面交互彩色体数据切割方法

基于代理多边形的3D纹理映射体绘制成像速度快,能够直接利用OpenGL剪切平面功能实现多平面实时切割,但成像质量不高.本文通过分析彩色数据场的不透明度转换函数,研究基于GPU的光线投射算法,用于数字人彩色体数据的快速高质量可视化.为了避免转换函数设计困难和不足,提出一种基GPU的多平面快速切割算法,能够实时清晰观察彩色体数据内部组织.实验结果表明:基于GPU的光线投射算成像质量高、速度快,该多平面交互切割方法能够清晰观察组织结构.     

An Initial Evaluation of Approaches to Building Entry for Large Robot Teams

Teams of robots offer potential reductions in risk for rescuers and improved rescue rates for search and rescue in collapsed buildings and other restricted environments. However, one aspect of deployment of such teams that is often overlooked is the initial entry of the robots into the building. If many robots enter the building from the same entrance, they are likely to interfere with each other and dramatically slow the initial phase of exploration. In this paper, we use a low fidelity simulation to evaluate several approaches to overcoming this initial congestion and identify heuristics that might allow the robots to most quickly clear the entry area and begin their actual mission. Our results show that unless the exits to the initial entry area are small, over a wide range of parameters, the most effective technique was for every robot to move in the direction of the longest open space it senses. In more cluttered environments with smaller exits, wall following, a strategy less dependent on the quality of sensing, proved more effective. Informal comparisons of these algorithms in a high fidelity simulation with limited trials and no variation in parameters suggested that simply promoting dispersion might be a more effective strategy for realistically complex dynamics.     

Enhancing N-Gram Based Metrics with Semantics for Better Evaluation of Abstractive Text Summarization

Text summarization is an important task in natural language processing and it has been applied in many applications. Recently, abstractive summarization has attracted many attentions. However, the traditional evaluation metrics that consider little semantic information, are unsuitable for evaluating the quality of deep learning based abstractive summarization models, since these models may generate new words that do not exist in the original text. Moreover, the out-of-vocabulary (OOV) problem that affects the evaluation results, has not been well solved yet. To address these issues, we propose a novel model called ENMS, to enhance existing N-gram based evaluation metrics with semantics. To be specific, we present two types of methods: N-gram based Semantic Matching (NSM for short), and N-gram based Semantic Similarity (NSS for short), to improve several widely-used evaluation metrics including ROUGE (Recall-Oriented Understudy for Gisting Evaluation), BLEU (Bilingual Evaluation Understudy), etc. NSM and NSS work in different ways. The former calculates the matching degree directly, while the latter mainly improves the similarity measurement. Moreover we propose an N-gram representation mechanism to explore the vector representation of N-grams (including skip-grams). It serves as the basis of our ENMS model, in which we exploit some simple but effective integration methods to solve the OOV problem efficiently. Experimental results over the TAC AESOP dataset show that the metrics improved by our methods are well correlated with human judgements and can be used to better evaluate abstractive summarization methods.     

Applications of a New Property of Conics to Architecture: An Alternative Design Project for Rio de Janeiro Metropolitan Cathedral

This paper describes the mathematical discovery of a new property of conics which allows the development of numerous geometric projects for use in architectural and engineering applications. Illustrated is an architectural application in the form of an alternative project for Río de Janeiro Metropolitan Cathedral featuring the integration of a circular base and a cross in the top plane. Two alternative designs are presented for the cathedral, based on the choice of either the Latin Immisa or Greek cross.     

Feature Detection Performance Based Benchmarking of Motion Deblurring Methods: Applications to Vision for Legged Robots

Dexterous legged robots can move on variable terrain at high speeds. The locomotion of these legged platforms on such terrain causes severe oscillations of the robot body depending on the surface and locomotion speed. Camera sensors mounted on such platforms experience the same disturbances, hence resulting in motion blur. This is a particular corruption of the image and results in information loss further resulting in degradation or loss of important image features. Although motion blur is a significant problem for legged mobile robots, it is of more general interest since it is present in many other handheld/mobile camera applications. Deblurring methods exist in the literature to compensate for blur, however most proposed performance metrics focus on the visual quality of compensated images. From the perspective of computer vision algorithms, feature detection performance is an essential factor that determines vision performance. In this study, we claim that existing image quality based metrics are not suitable to assess the performance of deblurring algorithms when the output is used for computer vision in general and legged robotics in particular. For comparatively evaluating deblurring algorithms, we define a novel performance metric based on the feature detection accuracy on sharp and deblurred images. We rank these algorithms according to the new metric as well as image quality based metrics from the literature and experimentally demonstrate that existing metrics may not be good indicators of algorithm performance, hence good selection criteria for computer vision application. Additionally, noting that a suitable data set to evaluate the effects of motion blur and its compensation for legged platforms is lacking in the literature, we develop a comprehensive multi-sensor data set for that purpose. The data set consists of monocular image sequences collected in synchronization with a low cost MEMS gyroscope, an accurate fiber optic gyroscope and an externally measured ground truth motion data. We make use of this data set for an extensive benchmarking of prominent motion deblurring methods from the literature in terms of existing and the proposed feature based metric.     

数传电台与GPRS相结合的水厂遥控系统研究和设计

针对城镇水厂供水系统,采用数传电台与GPRS相结合的远程遥控方式,完成井群水泵控制及供水管网流量压力等相关参数采集和传输;此外,根据供水管网分布广、管线长、管道泄漏精确定位难的特点,提出负压力波-流量法诊断供水管网泄漏的方案,实现供水系统参数实时采集、处理、无线传输及远程监控等功能。     

Digital enhancement of television signals for people with visual impairments: Evaluation of a consumer product

Abstract— Technology to improve the clarity of video for home‐theater viewers is available utilizing a low‐cost enhancement chip (DigiVision DV1000). The impact of such a device on the preference for enhanced video was tested for people with impaired vision and normally sighted viewers. Viewers with impaired vision preferred the enhancement effects more than normally sighted viewers. Preference for enhancement was correlated with loss in contrast sensitivity and visual acuity. Preference increased with increased enhancement settings (designed for those with normal vision) in the group with vision impairments. This suggests that higher enhancement levels may be of even greater benefit, and a similar product could be designed to meet the needs of the large, growing population of elderly television viewers with impaired vision.     

Maximum Principle for Optimal Boundary Control of Vibrating Structures with Applications to Beams

A maximum principle is derived for open-loop boundary control of one dimensional structures undergoing transverse vibrations. The optimal control law is obtained using a maximum principle and the applicability of the results to the boundary control of vibrating beams is demonstrated. The method of solution involves the transformation of the original problem into one with homogeneous boundary conditions for a general set of boundary forces and torques. An adjoint variable is introduced and used in the formulation of a Hamiltonian function which in turn leads to the derivation of the maximum principle. The effectiveness of the proposed control mechanism is illustrated numerically and it is shown that the implementation of the optimal boundary control using one force actuator can lead to substantial decrease in the dynamic response of a vibrating beam.     

Methods for adaptive combination of classifiers with application to recognition of handwritten characters

This paper discusses two techniques for improving the recognition accuracy for online handwritten character recognition: committee classification and adaptation to the user. Combining classifiers is a common method for improving recognition performance. Improvements are possible because the member classifiers may make different errors. Much variation exists in handwritten characters, and adaptation is one feasible way of dealing with such variation. Even though adaptation is usually performed for single classifiers, it is also possible to use adaptive committees. Some novel adaptive committee structures, namely, the dynamically expanding context (DEC), modified current best learning (MCBL), and class-confidence critic combination (CCCC), are presented and evaluated. They are shown to be able to improve on their member classifiers, with CCCC offering the best performance. Also, the effect of having either more or less diverse sets of member classifiers is considered.Received: 17 September 2002, Accepted: 22 October 2002, Published online: 4 July 2003     

Geometrical Optimization of Parallel Mechanisms Based on Natural Frequency Evaluation: Application to a Spherical Mechanism for Future Space Applications

This paper presents an optimization procedure conceived to design parallel mechanisms (PMs) with legs of constant and/or variable length connected, at their endpoints, to a fixed base and a movable platform through universal and spherical joints, respectively. In the proposed procedure, the first natural frequency of the mechanism is the objective function to be maximized. The optimization problem is formulated by using dimensionless variables in order to identify the optimal geometry independently of mechanism size, platform density, and leg cross-sectional area and material. As a case study, the procedure is employed to find the optimal geometry of a 2-DOF spherical PM to be used as an orienting device in future space missions.      

Greedy Geometric Algorithms for Collection of Balls,with Applications to Geometric Approximation and Molecular Coarse‐Graining

Choosing balls that best approximate a 3D object is a non‐trivial problem. To answer it, we first address the inner approximation problem, which consists of approximating an object defined by a union of n balls with balls defining a region . This solution is further used to construct an outer approximation enclosing the initial shape, and an interpolated approximation sandwiched between the inner and outer approximations. The inner approximation problem is reduced to a geometric generalization of weighted max k‐cover, solved with the greedy strategy which achieves the classical lower bound. The outer approximation is reduced to exploiting the partition of the boundary of by the Apollonius Voronoi diagram of the balls defining the inner approximation. Implementation‐wise, we present robust software incorporating the calculation of the exact Delaunay triangulation of points with degree two algebraic coordinates, of the exact medial axis of a union of balls, and of a certified estimate of the volume of a union of balls. Application‐wise, we exhibit accurate coarse‐grain molecular models using a number of balls 20 times smaller than the number of atoms, a key requirement to simulate crowded cellular environments.     

A workflow for handling heterogeneous 3D models with the TOUGH2 family of codes: Applications to numerical modeling of CO2 geological storage

This paper is addressed to the TOUGH2 user community. It presents a new tool for handling simulations run with the TOUGH2 code with specific application to CO₂ geological storage. This tool is composed of separate FORTRAN subroutines (or modules) that can be run independently, using input and output files in ASCII format for TOUGH2. These modules have been developed specifically for modeling of carbon dioxide geological storage and their use with TOUGH2 and the Equation of State module ECO2N, dedicated to CO₂-water-salt mixture systems, with TOUGHREACT, which is an adaptation of TOUGH2 with ECO2N and geochemical fluid-rock interactions, and with TOUGH2 and the EOS7C module dedicated to CO₂-CH₄ gas mixture is described. The objective is to save time for the pre-processing, execution and visualization of complex geometry for geological system representation. The workflow is rapid and user-friendly and future implementation to other TOUGH2 EOS modules for other contexts (e.g. nuclear waste disposal, geothermal production) is straightforward. Three examples are shown for validation: (i) leakage of CO₂ up through an abandoned well; (ii) 3D reactive transport modeling of CO₂ in a sandy aquifer formation in the Sleipner gas Field, (North Sea, Norway); and (iii) an estimation of enhanced gas recovery technology using CO₂ as the injected and stored gas to produce methane in the K12B Gas Field (North Sea, Denmark).     

Evaluation of multiple muscle loads through multi-objective optimization with prediction of subjective satisfaction level: Illustration by an application to handrail position for standing

Proposed here is an evaluation of multiple muscle loads and a procedure for determining optimum solutions to ergonomic design problems. The simultaneous muscle load evaluation is formulated as a multi-objective optimization problem, and optimum solutions are obtained for each participant. In addition, one optimum solution for all participants, which is defined as the compromise solution, is also obtained. Moreover, the proposed method provides both objective and subjective information to support the decision making of designers. The proposed method was applied to the problem of designing the handrail position for the sit-to-stand movement. The height and distance of the handrails were the design variables, and surface electromyograms of four muscles were measured. The optimization results suggest that the proposed evaluation represents the impressions of participants more completely than an independent use of muscle loads. In addition, the compromise solution is determined, and the benefits of the proposed method are examined.