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Visualizing Targeted Audiences

Social Query Interface Users of social networks can be passionate about sharing their political convictions, art projects or business ventures. They often want to direct their social interactions to certain people in order to start collaborations or to raise awareness about issues they support. However, users generally have scattered, unstructured information about the characteristics of their audiences, making it difficult for them to deliver the right messages or interactions to the right people. Existing audience-targeting tools allow people to select potential candidates based on predefined lists, but the tools provide few insights about whether or not these people would be appropriate for a specific type of communication. We have introduced an online tool, \textit{Hax}, to explore the idea of using interactive data visualizations to help people dynamically identify audiences for their different sharing efforts. We are providing the results of a preliminary empirical evaluation that shows the strength of the idea and points to areas for future research.

Directed Social Queries With Transparent User Models

The friend list of many social network users can be very large. This creates challenges when users seek to direct their social interactions to friends that share a particular interest or have the potential of being able to answer a particular question. We are presenting a self-organizing online tool that through incorporating ideas from user modeling and data visualization allows a person to quickly identify which friends’ best match a social query, enabling precise and efficient directed social interactions. To cover the different modalities in which our tool might be used, we are introducing two different interactive visualizations. One view enables a human-in-the-loop approach for result analysis and verification, and, in a second view, location, social affiliations and "personality" data is incorporated, allowing the user to quickly consider different social and spatial factors when directing social queries. We are reporting on a qualitative analysis, which indicates that transparency leads to an increased effectiveness of the system. This work contributes a novel method for exploring online friends.

Location Based Context Aware Recommendation System

Visual of I'm Feeling Loco Recommendation System Research in ubiquitous location recommendation systems has focused on automatically inferring a users’ preferences while little attention has been devoted to the recommendation algorithms. Location recommendation systems with a focus on recommendation algorithms generally require the user to complete complicated and time-consuming surveys and rarely consider the users current context. The purpose of this investigation is to design a more complete ubiquitous location-based recommendation algorithm that, by inferring users’ preferences and considering time geography and similarity measurements automatically, betters the user experience. Our system learns user preferences by mining a person’s social network profile. The physical constraints are delimited by a user’s location, and form of transportation, which is automatically detected through the use of a decision tree followed by a discrete Hidden Markov Model. We defined a decision-making model, which considers the learned preferences, physical constraints and how the individual is currently feeling. Our recommendation algorithm is based on a text classification problem. The detection of the form of transportation and the user interface was implemented on the Nokia N900 phone, the recommendation algorithm was implemented on a server that communicates with the phone. The novelty of our approach relies on the fusion of information inferred from a user’s social network profile and his/her mobile phones sensors for place discovery.

Enchantment Under the Sea: An Intelligent Environment for Music Mixing

Disc jockeys generally mix music in a confined isolated space. This can make the DJ have depression sentiments and it can also impact the DJ's understanding of his public. We present Enchantment Under The Sea, a new intelligent environment that allows DJs to roam freely, interact directly with his audience, receive informative feedback about the public's social interactions, while respecting the DJ’s privacy concerns. The music interface is controlled using Microsoft’s wireless touch mouse with ubiquitous gestures that resemble dance moves. The music mixing interface is displayed on the walls of the event, where two different display modalities are enabled: open interface, in which the public can observe all of the DJ’s decisions with the music mixing interface and also actively give music suggestions to the DJ, and a closed interface, where all the music controllers are mapped to sea animals, that only the DJ knows the mapping to, thus providing privacy to the DJ’s work. The public's social interactions are measured with sonar sensors whose data is provided to the DJ through the musical interface. We will report results of a controlled usability inspection.

Mmmmm: A Multi-Modal Musical Mobile Mixer

Mock-Up of Multi-Modal Musical Mobile Mixer Mmmmm stands for multi-modal musical mobile mixer and it is a new musical DJ application that has been designed for the Nokia N900 phone. This software enables a new type of interaction between the DJ and the crowd. Mmmmm has streaming via Bluetooth of the music generated in the phone to wireless speakers, which allows the DJ to move about the environment and get familiarized with the crowd, turning the experience of DJing into an interactive and audience-engaging process. It also has eyes-free mode enabled and it is carried out through hand gestures and haptic feedback, which allows the DJ to focus on the public and have a better intuition of what they are feeling. Mmmmm also has a "party detection" mode. By using the phone camera, the party scene is scanned and then a certain type of music as well as a series of songs is suggested. This mode helps novice DJs to instantly have a much better music repertoire, creating the illusion that an expert DJ is selecting the music the crowd is dancing to. Eyes-free mixing can be enabled at the wish of the user.

Wii Remote for Arm and Risk Therapy in Stroke Survivors

The Nintendo Wii remote is a compact, readily accessible position, orientation and motion-sensing technology with blue tooth wireless communication. We integrated the 3D position sensor to a gesture therapy system of computer simulated therapy exercises, which had previously been developed. We have also used pitch, yaw and roll, from the Wii remote 3D accelerometer to navigate a fly-through of an arbitrary Direct-X generated terrain. The hardware-based orientation and motion-sensing capabilities of the Wii remote complement vision-based systems and interface well with wrist exercises. The Wii remote model is promising for integration into clinical and home-based rehabilitation exercise therapy systems.

Time Scheduling Using a Genetic Algorithm

Photo of the School of Engineering of the National Autonomous University of Mexico The School of Engineering of the National Autonomous University of Mexico has more than 10,000 students. This large number of students requires the availability of a large number of courses. How do you schedule these courses in the most optimal way? What criteria would you use to say that one solution was better than the other? We proposed to solve this problem by means of a genetic algorithm. What we optimized was the time a classroom was utilized, i.e., we wanted to have continuous classes assigned to it throughout the day and know the schedule of each course. We considered that an optimal solution would have courses from the same semester and the same career assigned in rooms that were nearby to each other and in contiguous schedules since this would be beneficial for the students. In our proposed solution we also took into consideration the problem of having two different courses assigned in the same time slot or one professor assigned to two different courses in the same time period.