A multimodal restaurant finder for semantic web

Multimodal dialogue systems provide multiple modalities in the form of speech, mouse clicking, drawing or touch that can enhance human-computer interaction. However, one of the drawbacks of the existing multimodal systems is that they are highly domain-specific and they do not allow information to be shared across different providers. In this paper, we propose a semantic multimodal system, called Semantic Restaurant Finder, for the Semantic Web in which the restaurant information in different city/country/language are constructed as ontologies to allow the information to be sharable. From the Semantic Restaurant Finder, users can make use of the semantic restaurant knowledge distributed from different locations on the Internet to find the desired restaurants

A Multitask Data-Driven Model for Battery Remaining Useful Life Prediction

Lithium-ion batteries (LIBs) have recently been used widely in moving devices. Understand status of the batteries can help to predict the failure and improve the effectiveness of using them. There are some lithium-ion information that define the battery health over time. These are state-of-charge (SOC), state-of-health (SOH), and remaining-useful-life (RUL). Normally, a LIB is working under charging and discharging cycles continuously. In this paper, we will focus on the data dependency of different time-slots in a cycle and in a sequence of cycles to retrieve RUL. We leverage multi-channel inputs such as temperature, voltage, current and the nature of peaks cross the cycles to improve our prediction. Comparing to existing methods, the experiments show that we can improve from 0.040 to 0.033 (reduce 17.5%) in RMSE loss, which is significant

A MAS Negotiation Support Tool for Schema Matching

demo paperInternational audienceDatabase schema matching is the process of establishing correspondences between attributes of schemas for data integration purpose. Though various commercial tools have been developed, their results are inherently uncertain. In practice, to obtain correct attribute correspondences, there is a need for collecting human input, after the use of automatic matching tools, to reconcile erroneous mappings. We present a negotiation support tool that enables not a single expert but an expert team, whose members might have conflicting views, can work collaboratively to reconcile the output of the automatic tools. In an attempt to facilitate and support cooperation in team integration, our tool sets the goal to compute all possible decisions from expert inputs as well as explanations for each decision. Moreover, it also shows the foreseeable consequences of choosing a particular decision. Technically, this tool is developed on top of an argumentation framework

Physical therapy for sleep apnea: a smartphone application for home-based physical therapy for patients with obstructive sleep apnea

PurposeIn this study, we described “PT for Sleep Apnea”, a smartphone application for home-based physical therapy of patients with Obstructive Sleep Apnea (OSA).MethodsThe application was created in a joint program between the University of Medicine and Pharmacy at Ho Chi Minh City (UMP), Vietnam, and National Cheng Kung University (NCKU), Taiwan. Exercises maneuvers were derived from the exercise program previously published by the partner group at National Cheng Kung University. They included exercises for upper airway and respiratory muscle training and general endurance training.ResultsThe application provides video and in-text tutorials for users to follow at home and a schedule function to assist the user in organizing the training program, which may improve the efficacy of home-based physical therapy in patients with Obstructive Sleep Apnea.ConclusionIn the future, our group plans to conduct a user study and randomized-controlled trials to investigate whether our application can benefit patients with OSA

An ensemble approach for semantic assessment of summary writings

Computer-assisted assessment of summary writings is a challenging area which has recently attracted much interest from the research community. This is mainly due to the advances in other areas such as information extraction and natural language processing which have made automatic summary assessment possible. Different techniques such as Latent Semantic Analysis, $n$-gram co-occurrence and BLEU have been proposed for automatic evaluation of summaries. However, these techniques are unable to achieve good performance. In this paper, we propose an ensemble approach, that integrates two of the most effective summary evaluation techniques, LSA and n-gram co-occurrence, for improving the accuracy of automatic summary assessment. The performance of the proposed ensemble approach has shown that it is able to achieve high accuracy and improve the performance quite substantially compared with other existing techniques

Automatic summary assessment for intelligent tutoring systems

Summary writing is an important part of many English Language Examinations. As grading students' summary writings is a very time-consuming task, computer-assisted assessment will help teachers carry out the grading more effectively. Several techniques such as latent semantic analysis (LSA), n-gram co-occurrence and BLEU have been proposed to support automatic evaluation of summaries. However, their performance is not satisfactory for assessing summary writings. To improve the performance, this paper proposes an ensemble approach that integrates LSA and n-gram co-occurrence. As a result, the proposed ensemble approach is able to achieve high accuracy and improve the performance quite substantially compared with current techniques. A summary assessment system based on the proposed approach has also been developed