Factors influencing feature usage in work-related communication

Two studies are presented. The first aimed to identify possible barriers to the uptake and use of commonly available telephony features and to determine whether greater knowledge of features/access codes and availability of user manuals could increase feature usage under certain conditions. Results showed that feature-usage patterns were not affected by any of the manipulations, but that they were determined by specific job demands. Using Constantine and Lockwood's (1999) conceptualization of user roles, a method to support feature bundling decisions for specific target markets was developed and tested in the second study. The method - Strategic User Needs Analysis (SUNA) - was shown to yield a useful balance between high- and low-level information about selected roles. SUNA provided sufficient information to distinguish between PDA feature usage patterns of two similar target user groups as well as to suggest additional features each of the two target groups would find useful. The development of SUNA and observational findings of actual PDA usage are reported.     

QoS Negotiation and Renegotiation Based on Mobile Agents

As the Quality of Service （QoS） becomes increasingly important in the Internet development, there are more and more researches focusing on the issues of QoS negotiation. Mobile software agents represent a valid alternative to the implementation of strategies for the negotiation. In this paper, a QoS negotiation and renegotiation system architecture based on mobile agents is proposed. These agents perform the task in the whole process and therefore reduce the network load, overcome latency, and avoid frequent exchange information between clients and server. The simulation results show that it can improve the network resource utility about 10%.     

美孚油回收利用的可行性实验研究

本文针对美孚油回收液与兰炼8#油混合利用进行可行性实验研究，经过重度、粘度、可燃性等方面的实验研究，表明美孚油回收液与兰炼8#油混合可以用在电动轮上并且获得良好的效果。     

Accurate estimation of environment parameters from ultrasonic data

This paper describes a robust and accurate ultrasonic sensing system for a mobile robot. The system continuously updates a local map of the environment in which obstacles are represented by straight lines or points in a robot centered coordinate frame. The presented algorithms use a Kalman filter for the reduction of the noise in the ultrasonic data and use a systematical error correction (‘bundle correction’) to reduce the uncertainty in obstacle direction. Experiments are carried out in simulation and with a real mobile robot system. Results show that the accuracy with which line parameters can be estimated is in the order of 1 degree for the orientation and about 2 cm for the position. The effect of the bundle correction is significant and maximal when the robot approaches walls under a small angle.     

移动运营商渠道管理模式及存在问题分析

渠道作为营销体系中的重要一环，对移动运营商的发展起着举足轻重的作用。随着国内移动市场竞争的加剧，营销渠道的竞争将成为移动运营商间竞争的焦点。目前，国内两大移动运营商在渠道管理上存在诸多问题，从而影响了其市场拓展。分析了移动选营商渠道管理存在的三个较为突出的问题，并提出了可行的解决方法，从而为移动运营商的渠道管理工作提供思路。     

Echolocation — From range to outline segments

A ring of ultrasonic sensors mounted on a mobile robot is used to map a room. The sensors are modelled with an arc model: the object causing the reflection lies on an arc with radius equal to the range and arc angle equal to twice the beam angle. By fusing sensing with motion, a surface is displayed as a sequence of arcs. In this paper, the algorithm for obtaining outline segments from the arcs is presented.     

Mobile learning in chemical engineering: An outlook based on case studies

In the context of the electronic learning (E-learning) methodology, mobile learning (M-learning) focuses on the use of portable technology (such as mobiles or tablets) and the mobility of students. E-learning, and particularly M-learning, can be implemented in combination with other pedagogical methodologies for chemical engineering teaching and learning. We can consider that the vast majority of undergraduates own personal mobile devices nowadays. Moreover, many case studies have shown that M-learning is an effective methodology to capture students’ attention and to actively engage them in the learning process. In most cases, lecturers have reported an improvement in both academic performance and qualifications and have expressed a favourable opinion towards this type of initiative in surveys. In line with the increasing interest in the incorporation of E-learning, this review discusses cases studies based on M-learning within the field of chemical engineering teaching through different technological platforms and apps which can be installed or directly used on mobile devices. All the platforms described in this work offer a free version, emphasizing the possibility of extending this methodology within the university with no need for additional economic resources.     

云测试综述

针对云计算的定义及云计算的特点做出分析。认为云计算有着良好的发展趋势,并在次基础上展开对云测试的讨论,主要涉及云测试的特点、优点、应用现状,云测试平台以及云测试技术,并探讨云测试的对现有测试服务模式的影响及存在的缺陷,预测云测试的发展趋势。     

A bacterial colony growth algorithm for mobile robot localization

Achieving robot autonomy is a fundamental objective in Mobile Robotics. However in order to realize this goal, a robot must be aware of its location within an environment. Therefore, the localization problem (i.e.,the problem of determining robot pose relative to a map of its environment) must be addressed. This paper proposes a new biology-inspired approach to this problem. It takes advantage of models of species reproduction to provide a suitable framework for maintaining the multi-hypothesis. In addition, various strategies to track robot pose are proposed and investigated through statistical comparisons. The Bacterial Colony Growth Algorithm (BCGA) provides two different levels of modeling: a background level that carries on the multi-hypothesis and a foreground level that identifies the best hypotheses according to an exchangeable strategy. Experiments, carried out on the robot ATRV-Jr manufactured by iRobot, show the effectiveness of the proposed BCGA.

RoadCompass: following rural roads with vision + ladar using vanishing point tracking

We present a vision- and ladar-based approach to autonomous driving on rural and desert roads that has been tested extensively in a closed-loop system. The vision component uses Gabor wavelet filters for texture analysis to find ruts and tracks from which the road vanishing point can be inferred via Hough-style voting, yielding a direction estimate for steering control. The ladar component projects detected obstacles along the road direction onto the plane of the front of the vehicle and tracks the 1-D obstacle “gap” presumed due to the road to yield a lateral offset estimate. Several image- and state-based tests to detect failure conditions such as off-road poses (i.e., there is no road to follow) and poor lighting due to sun glare or distracting shadows are also explained. The system’s efficacy is demonstrated with analysis of diverse logged data including from the 2005 DARPA Grand Challenge, as well as tests with full control of a vehicle over 15 km of difficult roads at up to 37 km/h with no waypoints.