Various information displays are becoming available for implementing new kinds of human computer interaction (HCI) methods. Among many types and models, touch panel displays have been used in wide range of application...
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Various information displays are becoming available for implementing new kinds of human computer interaction (HCI) methods. Among many types and models, touch panel displays have been used in wide range of applications and are proven to be a useful infrastructure for creating intuitive HCI. In spite of their popularity, there are some weak points. The most serious drawback is their hardness to operate especially for the weak in information technology such as elderly and blind users. A tactile feedback function has a potential ability for enabling them to make full use of the devices. We propose an approach for effectively designing user-friendly HCI based on the tactile feedback. We exemplify our approach through the design and development of a few practical applications, an electronic voting system and a disaster information exploration system. The applications are targeted at supporting the weak, but the touch interactions quite are useful for general public for improving the stability and the degree of satisfaction in operations. These systems use a touch panel haptic display for helping the users to operate with straightforward touch sensations. It allows them to easily confirm, select, and activate their desired functions. We also conducted some evaluations to verify the effectiveness of the proposed framework.
In this paper, a new type of autonomous vehicle is developed. This vehicle consists of three sets of control systems to regulate the direction, brake and fuels. The sensing system is a combination of laser radar and c...
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In this paper, a new type of autonomous vehicle is developed. This vehicle consists of three sets of control systems to regulate the direction, brake and fuels. The sensing system is a combination of laser radar and camera. The localization system is constructed with GPS device and electronically compass. Currently, three tasks, including lane detection and following, object detection, and obstacle avoidance, has been implemented on this platform. We reported some experimental results.
Most existing camera placement algorithms focus on coverage and/or visibility analysis, which ensures that the object of interest is visible in the camera's field of view (FOV). According to recent literature, han...
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Most existing camera placement algorithms focus on coverage and/or visibility analysis, which ensures that the object of interest is visible in the camera's field of view (FOV). According to recent literature, handoff safety margin is introduced to sensor planning so that sufficient overlapped FOVs among adjacent cameras are reserved for successful and smooth target transition. In this paper, we investigate the sensor planning problem when considering the dynamic interactions between moving targets and observing cameras. The probability of camera overload is explored to model the aforementioned interactions. The introduction of the probability of camera overload also considers the limitation that a given camera can simultaneously monitor or track a fixed number of targets and incorporates the target's dynamics into sensor planning. The resulting camera placement not only achieves the optimal balance between coverage and handoff success rate but also maintains the optimal balance in environments with various target densities. The proposed camera placement method is compared with a reference algorithm by Erdem and Sclaroff. Consistently improved handoff success rate is illustrated via experiments using typical office floor plans with various target densities.
Multiple instance (MI) learning is a recent learning paradigm that is more flexible than standard supervised learning algorithms in the handling of label ambiguity. It has been used in a wide range of applications inc...
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Multiple instance (MI) learning is a recent learning paradigm that is more flexible than standard supervised learning algorithms in the handling of label ambiguity. It has been used in a wide range of applications including image classification, object detection and object tracking. Typically, MI algorithms are trained in a batch setting in which the whole training set has to be available before training starts. However, in applications such as tracking, the classifier needs to be trained continuously as new frames arrive. Motivated by the empirical success of a batch MI algorithm called MILES, we propose in this paper an online MI learning algorithm that has an efficient online update procedure and also performs joint feature selection and classification as MILES. Besides, while existing online MI algorithms lack theoretical properties, we prove that the proposed online algorithm has a (cumulative) regret of O(√T), where T is the number of iterations. In other words, the average regret goes to zero asymptotically and it thus achieves the same performance as the best solution in hindsight. Experiments on a number of MI classification and object tracking data sets demonstrate encouraging results.
Most existing performance evaluation methods concentrate on defining separate metrics over a wide range of conditions and generating standard benchmarking video sequences for examining the effectiveness of video track...
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In this work a decision support tool for optimal administration of Levodopa (L-Dopa) in patients with Parkinson's Disease (PD) is presented. The so called Medication Change Proposer (MCP) is part of the PERFORM sy...
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Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. However, the PSO algorithm suffers from premature convergence and high ...
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Our goal is to understand limitations of simplicity of knowledge structures and reasoning processes in Multiagent systems. Therefore, we propose a framework that integrates external storage media and a capacity-constr...
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Our goal is to understand limitations of simplicity of knowledge structures and reasoning processes in Multiagent systems. Therefore, we propose a framework that integrates external storage media and a capacity-constrained Multiagent System. Agents can store knowledge internally and on external storage media located in an environment. In some cases, agents either have to forget or to store knowledge externally due to limited internal memory. We define notions of suitable knowledge and let agents learn in the context of an iterative partitioning task problem. Using basic knowledge structures and a simple k-Nearest-Neighbor approach, we evaluate the role of limited internal memory in conjunction with strategic positioning of storage media and knowledge items. We also investigate dependencies between communication, internal memory size, frequently changing settings, and externally stored items. The results show that externally and strategically stored simple knowledge can support agents' reasoning processes. The approach is robust even in highly dynamic settings with small memory and without inter-agent communication.
Energy storage is generally recommended in presence of an intermittent source like wind farm for a better control over the power generation from the wind turbine with the variation of the wind speed. In this paper, th...
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Energy storage is generally recommended in presence of an intermittent source like wind farm for a better control over the power generation from the wind turbine with the variation of the wind speed. In this paper, the potential of plug-in electric vehicle parking lot (SmartPark) as an energy storage in a power system with a large wind farm has been investigated. Also, a fuzzy logic based coordination controller of the wind farm and the distributed SmartParks has been proposed in this paper. The fuzzy controller uses the total state-of-charge of the SmartParks and the difference between instantaneous demand and the available wind power generation as the inputs and thereby generates the charging or discharging power commands of the SmartParks and the pitch angle reference for the wind turbine. A 12-bus multimachine power system with a 400 MW wind farm is used as a test system. Six SmartParks are also connected to the same bus where the wind farm is connected. The entire model is developed in Real-Time Digital Simulator (RTDS) for power system. The results demonstrate the action of the coordinated controller to reduce the oscillations in the tie-line power flow with the sudden variations of the wind speed.
In this paper, we present an overview of a system that we are developing for the continuous monitoring of water distribution systems in Singapore. We discuss the design and implementation of the system that enables re...
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