Monika Akbar

The Role of Visualization in Computer Science Education

Computer science core instruction attempts to provide a detailed understanding of dynamic processes such as the working of an algorithm or the flow of information between computing entities. Such dynamic processes are not well explained by static media such as text and images, and are difficult to convey in lecture. The authors survey the history of visualization in computer science education, focusing on artifacts that have a documented positive educational assessment. Changes in how computing technology has affected the development and uptake of such visualization artifacts in computer science education, and how recent technology changes are leading to progress in developing online hypertextbooks are then discussed.

Ensemble PDP-8: eight principles for distributed portals

Ensemble, the National Science Digital Library (NSDL) Pathways project for Computing, builds upon a diverse group of prior NSDL, DL-I, and other projects. Ensemble has shaped its activities according to principles related to design, development, implementation, and operation of distributed portals. Here we articulate 8 key principles for distributed portals (PDPs). While our focus is on education and pedagogy, we expect that our experiences will generalize to other digital library application domains. These principles inform, facilitate, and enhance the Ensemble R&D and production activities. They allow us to provide a broad range of services, from personalization to coordination across communities. The eight PDPs can be briefly summarized as: (1) Articulation across communities using ontologies. (2) Browsing tailored to collections. (3) Integration across interfaces and virtual environments. (4) Metadata interoperability and integration. (5) Social graph construction using logging and metrics. (6) Superimposed information and annotation integrated across distributed systems. (7) Streamlined user access with IDs. (8) Web 2.0 multiple social network system interconnection.

Frequent pattern-growth approach for document organization

In this paper, we propose a document clustering mechanism that depends on the appearance of frequent senses in the documents rather than on the co-occurrence of frequent keywords. Instead of representing each document as a collection of keywords, we use a document-graph which reflects a conceptual hierarchy of keywords related to that document. We incorporate a graph mining approach with one of the well-known association rule mining procedures, FP-growth, to discover the frequent subgraphs among the document-graphs. The similarity of the documents is measured in terms of the number of frequent subgraphs appearing in the corresponding document-graphs. We believe that our novel approach allows us to cluster the documents based more on their senses rather than the actual keywords.

Narratives in the network: interactive methods for mining cell signaling networks.

In this article, we describe our work on graph mining as applied to the cellular signaling pathways in the Signal Transduction Knowledge Environment (STKE). We present new algorithms and a graphical tool that can help biologists discover relationships between pathways by looking at structural overlaps within the database. We address the problem of determining pathway relationships by using two data mining approaches: clustering and storytelling. In the first approach, our tool brings similar pathways to the same cluster, and in the second, our tool determines intermediate overlapping pathways that can lead biologists to new hypotheses and experiments regarding relationships between the pathways. We formulate the problem of discovering pathway relationships as a subgraph discovery problem and propose a new technique called Subgraph-Extension Generation (SEG), which outperforms the traditional Frequent Subgraph Discovery (FSG) approach by magnitudes. Our tool provides an interface to compare these two approaches with a variety of similarity measures and clustering techniques as well as in terms of computational performance measures such as runtime and memory consumption.

Recommendation based on deduced social networks in an educational digital library

Discovering useful resources can be difficult in digital libraries with large content collections. Many educational digital libraries (edu-DLs) host thousands of resources. One approach to avoiding information overload involves modeling user behavior. But this often depends on user feedback, along with the demographic information found in user account profiles, in order to model and predict user interests. However, edu-DLs often host collections with open public access, allowing users to navigate through the system without needing to provide identification. With few identifiable users, building models linked to user accounts provides insufficient data to recommend useful resources. Analyzing user activity on a per-session basis, to deduce a latent user network, can take place even without user profiles or prior use history. The resulting Deduced Social Network (DSN) can be used to improve DL services. An example of a DSN is a graph whose nodes are sessions and whose edges connect two sessions that view the same resource. In this paper we present a recommendation framework for edu-DLs that depends on deduced connections between users. Results show that a recommendation system built from DSN-dependent parameters can improve performance compared to when only text similarity between resources is used. Our approach can potentially improve recommendation for DL resources when implicit user activities (e.g., view, click, search) are abundant but explicit user activities (e.g., account creation, rating, comment) are unavailable.

Deduced social networks for an educational digital library

By analyzing the behavior of previous users, digital libraries can be made to provide new users with more support to find the best information. The AlgoViz Portal collects metadata on algorithm visualizations and associated research literature. We show how logs can be used to discover latent relationships between users, deducing an implicit social network. By clustering the log data, we find different page-viewing patterns, which provide practical information about the different groups of users.

Digital library 2.0 for educational resources

We report on focus group feedback regarding the services provided by existing education-related Digital Libraries (DL). Participants provided insight into how they seek educational resources online, and what they perceive to be the shortcomings of existing educational DLs. Along with useful content, social interactions were viewed as important supplements for educational DLs. Such interactions lead to both an online community and new forms of content such as reviews and ratings. Based on our analysis of the focus group feedback, we propose DL 2.0, the next generation of digital library, which integrates social knowledge with DL content.

Inexpensive construction of a 3D face model from stereo images

Construction of a three dimensional face model from stereo images is a challenging task. Most of the currently available systems for reconstruction of 3D models require special hardware for calibration. In this paper, we illustrate a mechanism to construct a three dimensional face model from two stereo images. The developed mechanism does not require any special devices to calibrate the stereo images. We used a hand-held inexpensive digital camera to take the stereo images of a face. We did not use any camera-stand to fix and measure the camera system geometry. The stereo images were taken holding the camera in hand and moving it to two slightly different viewpoints. We constructed a depth map from these two stereo images and utilized this depth map to reconstruct the three dimensional face model. The 3D face model reconstruction process described in this paper uses some existing theories and combines them to develop a new system to generate the depth map. The system requires minimal user interaction for the reconstruction.

Digital Technology Shaping Teaching Practices in Higher Education

In their quest on being effective, educators have always experimented with the art of teaching. Teaching has evolved over centuries by adopting new approaches, methods, tools, and technologies to reach a wider audience. As technologies advance, educators should carefully use, evaluate, and adopt the changes to utilize the technologies and track of their impacts. This article provides a mini review to briefly describe some of the existing technical achievements that are used in higher education along with their challenges.

Analyzing the acoustic urban environment: A geofencing-centered approach in the Curitiba Metropolitan Region, Brazil

The industrial development and Brazilian economic context led to important structural changes, among others, the increase of population migration (rural to urban spaces), number of private vehicles (due to tax reduction and state subsidies for new cars and fuel), among others. Such changes impact not only the urban mobility at big cities but also the urban life quality, which is directly affected by pollutant emissions and noise. In order to limit emission impacts on sensitive population (children, elderly people, for example), city managers can enforce bounds on emissions and noise pollution generated by the city traffic in specific regions defined by geographical boundaries. This paper aims to contribute to the challenge of managing urban noise by exploring and analyzing the data with a geofencing approach. In particular, we present a exploratory data analysis toward a case study in Curitiba (1,800,000 inhabitants, a southern Brazilian city) aiming at analyzing possible sources of noise based on a particular data set of noise measurements, geographical information data, traffic, transportation and city licensing data.