Evaluating design metrics on large-scale software

Design-quality metrics that are being developed for predicting the potential quality and complexity of the system being developed are discussed. The goal of the metrics is to provide timely design information that can guide a developer in producing a higher quality product. The metrics were tested on projects developed in a university setting with client partners in industry. To further validate the metrics, they were applied to professionally developed systems to test their predictive qualities. The results of applying two design metrics and a composite metric to data from a large-scale industrial project are presented     

A Framework for Interactive t-SNE Clustering

In this paper, we describe our progress in creating the framework for an interactive application that allows humans to actively participate in a t-SNE clustering process. t-SNE (t-Distributed Stochastic Neighbor Embedding) is a dimensionality reduction technique that maps high dimensional data sets to lower dimensions that can then be visualized for human interpretation. By prompting users to monitor outlying points during the t-SNE clustering process, we hypothesize that users may be able to make clustering faster and more accurate than purely algorithmic methods. Further research would test these hypotheses directly. We would also attempt to decrease the lag time between the various components of our application and develop an intuitive approach for humans to aid in clustering unlabeled data. Research into human assisted clustering can combine the strengths of both humans and computer programs to improve the results of data analysis.     

In-line holographic electron microscopy in the presence of external magnetic fields

It is now a well-known fact that the phase of electron waves is altered by external magnetic fields via the Aharonov-Bohm effect. This implies that any electron interference effects will be to some degree affected by the presence of such fields. In this study we examine the distortion effects of external (constant and variable) magnetic fields on electron interference and holography. For digital holography, the reconstruction of the object is done via numerical calculations and this leaves the door open for correcting phase distortions in the hologram reconstruction. We design and quantitatively assess such correction schemes, which decidedly depend on our knowledge of the magnetic field values in the holographic recording process. For constant fields of known value we are able to correct for magnetic distortions to a great extent. We find that variable fields are more destructive to the holographic process than constant fields. We define two criteria, related respectively to global and local contrast of the hologram to establish the maximum allowed external field which does not significantly hinder the accuracy of in-line holographic microscopy with electrons.     

On the complexity of deciding avoidability of sets of partial words

Blanchet-Sadri et al. have shown that Avoidability, or the problem of deciding the avoidability of a finite set of partial words over an alphabet of size k≥2, is NP-hard [F. Blanchet-Sadri, R. Jungers, J. Palumbo, Testing avoidability on sets of partial words is hard, Theoret. Comput. Sci. 410 (2009) 968-972]. Building on their work, we analyze in this paper the complexity of natural variations on the problem. While some of them are NP-hard, others are shown to be efficiently decidable. Using some combinatorial properties of de Bruijn graphs, we establish a correspondence between lengths of cycles in such graphs and periods of avoiding words, resulting in a tight bound for periods of avoiding words. We also prove that Avoidability can be solved in polynomial space, and reduces in polynomial time to the problem of deciding the avoidability of a finite set of partial words of equal length over the binary alphabet. We give a polynomial bound on the period of an infinite avoiding word, in the case of sets of full words, in terms of two parameters: the length and the number of words in the set. We give a polynomial space algorithm to decide if a finite set of partial words is avoided by a non-ultimately periodic infinite word. The same algorithm also decides if the number of words of length n avoiding a given finite set of partial words grows polynomially or exponentially with n.     

Steward: Scaling Byzantine Fault-Tolerant Replication to Wide Area Networks

This paper presents the first hierarchical Byzantine fault-tolerant replication architecture suitable to systems that span multiple wide-area sites. The architecture confines the effects of any malicious replica to its local site, reduces message complexity of wide-area communication, and allows read-only queries to be performed locally within a site for the price of additional standard hardware. We present proofs that our algorithm provides safety and liveness properties. A prototype implementation is evaluated over several network topologies and is compared with a flat Byzantine fault-tolerant approach. The experimental results show considerable improvement over flat Byzantine replication algorithms, bringing the performance of Byzantine replication closer to existing benign fault-tolerant replication techniques over wide area networks.     

From I-Awareness to We-Awareness in CSCW

Awareness is one of the central concepts in Computer Supported Cooperative Work, though it has often been used in several different senses. Recently, researchers have begun to provide a clearer conceptualization of awareness that provides concrete guidance for the structuring of empirical studies of awareness and the development of tools to support awareness. Such conceptions, however, do not take into account newer understandings of shared intentionality among cooperating actors that recently have been defined by philosophers and empirically investigated by psychologists and psycho-linguists. These newer conceptions highlight the common ground and socially recursive inference that underwrites cooperative behavior. And it is this inference that is often seamlessly carried out in collocated work, so easy to take for granted and hence overlook, that will require computer support if such work is to be partially automated or carried out at a distance. Ignoring the inferences required in achieving common ground may thus focus a researcher or designer on surface forms of “heeding” that miss the underlying processes of intention shared in and through activity that are critical for cooperation to succeed. Shared intentionality thus provides a basis for reconceptualizing awareness in CSCW research, building on and augmenting existing notions. In this paper, we provide a philosophically grounded conception of awareness based on shared intentionality, demonstrate how it accounts for behavior in an empirical study of two individuals in collocated, tightly-coupled work, and provide implications of this conception for the design of computational systems to support tightly-coupled collaborative work.     

A novel hardware plane fitting implementation and applications for bionic vision

This paper presents a high-speed real-time plane fitting implementation on a field-programmable gate array (FPGA) platform. A novel hardware-based least squares algorithm fits planes to patches of points within a depth image captured using a Microsoft Kinect v2 sensor. The validity of a plane fit and the plane parameters are reported for each patch of 11 by 11 depth pixels. The high level of parallelism of operations in the algorithm has allowed for a fast, low-latency hardware implementation on an FPGA that is capable of processing depth data at a rate of 480 frames per second. A hybrid hardware–software end-to-end system integrates the hardware solution with the Kinect v2 sensor via a computer and PCI express communication link to a Terasic TR4 FPGA development board. We have also implemented two proof-of-concept object detection applications as future candidates for bionic vision systems. We show that our complete end-to-end system is capable of running at 60 frames per second. An analysis and characterisation of the Kinect v2 sensor errors has been performed in order to specify logic precision requirements, statistical testing of the validity of a plane fit, and achievable plane fitting angle resolution.     

Student success prediction in MOOCs

Predictive models of student success in Massive Open Online Courses (MOOCs) are a critical component of effective content personalization and adaptive interventions. In this article we review the state of the art in predictive models of student success in MOOCs and present a categorization of MOOC research according to the predictors (features), prediction (outcomes), and underlying theoretical model. We critically survey work across each category, providing data on the raw data source, feature engineering, statistical model, evaluation method, prediction architecture, and other aspects of these experiments. Such a review is particularly useful given the rapid expansion of predictive modeling research in MOOCs since the emergence of major MOOC platforms in 2012. This survey reveals several key methodological gaps, which include extensive filtering of experimental subpopulations, ineffective student model evaluation, and the use of experimental data which would be unavailable for real-world student success prediction and intervention, which is the ultimate goal of such models. Finally, we highlight opportunities for future research, which include temporal modeling, research bridging predictive and explanatory student models, work which contributes to learning theory, and evaluating long-term learner success in MOOCs.