An Immersive Telepresence System using RGB-D Sensors and Head Mounted Display

We present a tele-immersive system that enables people to interact with each other in a virtual world using body gestures in addition to verbal communication. Beyond the obvious applications, including general online conversations and gaming, we hypothesize that our proposed system would be particularly beneficial to education by offering rich visual contents and interactivity. One distinct feature is the integration of egocentric pose recognition that allows participants to use their gestures to demonstrate and manipulate virtual objects simultaneously. This functionality enables the instructor to ef- fectively and efficiently explain and illustrate complex concepts or sophisticated problems in an intuitive manner. The highly interactive and flexible environment can capture and sustain more student attention than the traditional classroom setting and, thus, delivers a compelling experience to the students. Our main focus here is to investigate possible solutions for the system design and implementation and devise strategies for fast, efficient computation suitable for visual data processing and network transmission. We describe the technique and experiments in details and provide quantitative performance results, demonstrating our system can be run comfortably and reliably for different application scenarios. Our preliminary results are promising and demonstrate the potential for more compelling directions in cyberlearning.Comment: IEEE International Symposium on Multimedia 201

Towards virtual communities on the Web: Actors and audience

We report about ongoing research in a virtual reality environment where visitors can interact with agents that help them to obtain information, to perform certain transactions and to collaborate with them in order to get some tasks done. Our environment models a theatre in our hometown. We discuss attempts to let this environment evolve into a theatre community where we do not only have goal-directed visitors, but also visitors that that are not sure whether they want to buy or just want information or visitors who just want to look around. It is shown that we need a multi-user and multiagent environment to realize our goals. Since our environment models a theatre it is also interesting to investigate the roles of performers and audience in this environment. For that reason we discuss capabilities and personalities of agents. Some notes on the historical development of networked communities are included

User Intent Prediction in Information-seeking Conversations

Conversational assistants are being progressively adopted by the general population. However, they are not capable of handling complicated information-seeking tasks that involve multiple turns of information exchange. Due to the limited communication bandwidth in conversational search, it is important for conversational assistants to accurately detect and predict user intent in information-seeking conversations. In this paper, we investigate two aspects of user intent prediction in an information-seeking setting. First, we extract features based on the content, structural, and sentiment characteristics of a given utterance, and use classic machine learning methods to perform user intent prediction. We then conduct an in-depth feature importance analysis to identify key features in this prediction task. We find that structural features contribute most to the prediction performance. Given this finding, we construct neural classifiers to incorporate context information and achieve better performance without feature engineering. Our findings can provide insights into the important factors and effective methods of user intent prediction in information-seeking conversations.Comment: Accepted to CHIIR 201

Performance of grassed swale as stormwater quantity control in lowland area

Grassed swale is a vegetated open channel designed to attenuate stormwater through infiltration and conveying runoff into nearby water bodies, thus reduces peak flows and minimizes the causes of flood. UTHM is a flood-prone area due to located in lowland area, has high groundwater level and low infiltration rates. The aim of this study is to assess the performance of grassed swale as a stormwater quantity control in UTHM. Flow depths and velocities of swales were measured according to Six-Tenths Depth Method shortly after a rainfall event. Flow discharges of swales (Qswale) were evaluated by Mean- Section Method to determine the variations of Manning’s roughness coefficients (ncalculate) that results between 0.075 – 0.122 due to tall grass and irregularity of channels. Based on the values of Qswale between sections of swales, the percentages of flow attenuation are up to 54%. As for the flow conveyance of swales, Qswale were determined by Manning’s equation that divided into Qcalculate, evaluated using ncalculate, and Qdesign, evaluated using roughness coefficient recommended by MSMA (ndesign), to compare with flow discharges of drainage areas (Qpeak), evaluated by Rational Method with 10-year ARI. Each site of study has shown Qdesign is greater than Qpeak up to 59%. However, Qcalculate is greater than Qpeak only at a certain site of study up to 14%. The values of Qdesign also greater than Qcalculate up to 52% where it shows that the roughness coefficients as considered in MSMA are providing a better performance of swale. This study also found that the characteristics of the studied swales are comparable to the design consideration by MSMA. Based on these findings, grassed swale has the potential in collecting, attenuating, and conveying stormwater, which suitable to be applied as one of the best management practices in preventing flash flood at UTHM campus

Promoting New Patterns in Household Energy Consumption with Pervasive Learning Games

Engaging computer games can be used to change energy consumption patterns in the home. PowerAgent is a pervasive game for Java-enabled mobile phones that is designed to influence everyday activities and use of electricity in the domestic setting. PowerAgent is connected to the household’s automatic electricity meter reading equipment via the cell network, and this setup makes it possible to use actual consumption data in the game. In this paper, we present a two-level model for cognitive and behavior learning, and we discuss the properties of PowerAgent in relation to the underlying situated learning, social learning, and persuasive technology components that we have included in the game