Analysing information systems evaluation: another look at an old problem

Information systems (IS) evaluation is a thorny problem. In this paper we re-examine the area in light of recent developments in the field. Our examination begins with an example of a common contemporary IS assessment problem, viz. evaluating outsourcing. The example highlights the organizational and political issues that make evaluation fraught with difficulties. The paper argues that IS evaluation is a ‘necessary evil’ but the context in which IS are developed and used has become much more demanding and complex. A conceptual framework, first proposed in an earlier paper as a way to classify the literature, is presented and brought up to date. The framework is then used to re-examine the outsourcing example, demonstrating the usefulness of the framework.     

Mechanical principles of dynamic terrestrial self-righting using wings

Terrestrial animals and robots are susceptible to flipping-over during rapid locomotion in complex terrains. However, small robots are less capable of self-righting from an upside-down orientation compared to small animals like insects. Inspired by the winged discoid cockroach, we designed a new robot that opens its wings to self-right by pushing against the ground. We used this robot to systematically test how self-righting performance depends on wing opening magnitude, speed, and asymmetry, and modeled how kinematic and energetic requirements depend on wing shape and body/wing mass distribution. We discovered that the robot self-rights dynamically using kinetic energy to overcome potential energy barriers, that larger and faster symmetric wing opening increases self-righting performance, and that opening wings asymmetrically increases righting probability when wing opening is small. Our results suggested that the discoid cockroach’s winged self-righting is a dynamic maneuver. While the thin, lightweight wings of the discoid cockroach and our robot are energetically sub-optimal for self-righting compared to tall, heavy ones, their ability to open wings saves them substantial energy compared to if they had static shells. Analogous to biological exaptations, our study provided a proof-of-concept for terrestrial robots to use existing morphology in novel ways to overcome new locomotor challenges.     

A longitudinal study of emoticon use in text messaging from smartphones

Our goal in the present study was to understand how emoticons are used in text messaging and, in particular, how genders differed in the frequency and variety of emoticons used via this medium. Previous research has found small and sundry differences in emotive expression online suggesting that technology has closed the gender gap. However, the data collected in these studies were public. In this study, we collected real portions of private communications data from individuals’ smartphones over a 6-month period. SMS messages, in general, were not used very much overall, with only 4% of all messages containing at least one emoticon. Still, differences between genders manifested in the amount and variety of emoticons used. Females sent more messages with emoticons; however, surprisingly, males used a more diverse range of emoticons.     

Personalcasting: Tailored Broadcast News

Broadcast news sources and newspapers provide society with the vast majority of real-time information. Unfortunately, cost efficiencies and real-time pressures demand that producers, editors, and writers select and organize content for stereotypical audiences. In this article we illustrate how content understanding, user modeling, and tailored presentation generation promise personalcasts on demand. Specifically, we report on the design and implementation of a personalized version of a broadcast news understanding system, MITRE’s Broadcast News Navigator (BNN), that tracks and infers user content interests and media preferences. We report on the incorporation of Local Context Analysis to both expand the user’s original query to the most related terms in the corpus, as well as to allow the user to provide interactive feedback to enhance the relevance of selected newsstories. We describe an empirical study of the search for stories on ten topics from a video corpus. By personalizing both the selection of stories and the form in which they are delivered, we provide users with tailored broadcast news. This individual news personalization provides more fine-grained content tailoring than current personalized television program level recommenders and does not rely on externally provided program metadata.     

Interval Set Clustering of Web Users with Rough K-Means

Data collection and analysis in web mining faces certain unique challenges. Due to a variety of reasons inherent in web browsing and web logging, the likelihood of bad or incomplete data is higher than conventional applications. The analytical techniques in web mining need to accommodate such data. Fuzzy and rough sets provide the ability to deal with incomplete and approximate information. Fuzzy set theory has been shown to be useful in three important aspects of web and data mining, namely clustering, association, and sequential analysis. There is increasing interest in research on clustering based on rough set theory. Clustering is an important part of web mining that involves finding natural groupings of web resources or web users. Researchers have pointed out some important differences between clustering in conventional applications and clustering in web mining. For example, the clusters and associations in web mining do not necessarily have crisp boundaries. As a result, researchers have studied the possibility of using fuzzy sets in web mining clustering applications. Recent attempts have used genetic algorithms based on rough set theory for clustering. However, the genetic algorithms based clustering may not be able to handle the large amount of data typical in a web mining application. This paper proposes a variation of the K-means clustering algorithm based on properties of rough sets. The proposed algorithm represents clusters as interval or rough sets. The paper also describes the design of an experiment including data collection and the clustering process. The experiment is used to create interval set representations of clusters of web visitors.     

A multi-level cache model for run-time optimization of remote visualization

Remote visualization is an enabling technology aiming to resolve the barrier of physical distance. While many researchers have developed innovative algorithms for remote visualization, previous work has focused little on systematically investigating optimal configurations of remote visualization architectures. In this paper, we study caching and prefetching, an important aspect of such architecture design, in order to optimize the fetch time in a remote visualization system. Unlike a processor cache or web cache, caching for remote visualization is unique and complex. Through actual experimentation and numerical simulation, we have discovered ways to systematically evaluate and search for optimal configurations of remote visualization caches under various scenarios, such as different network speeds, sizes of data for user requests, prefetch schemes, cache depletion schemes, etc. We have also designed a practical infrastructure software to adaptively optimize the caching architecture of general remote visualization systems, when a different application is started or the network condition varies. The lower bound of achievable latency discovered with our approach can aid the design of remote visualization algorithms and the selection of suitable network layouts for a remote visualization system.     

A hybrid capacitive pressure and temperature sensor fabricated by adhesive bonding technique for harsh environment of kraft pulp digesters

We have developed a compensated capacitive pressure and temperature sensor for kraft pulp digesters (pH 13.5, temperatures 25–175°C reaching a local maximum of 180°C and pressures up to 2 MPa). The gauge capacitive pressure sensor was fabricated by bonding silicon and Pyrex chips using a high temperature, low viscosity UV (ultraviolent) adhesive as the gap-controlling layer and heat curing adhesive as the bonding agent. A simple chip bonding technique, involving insertion of the adhesive into the gap between two chips was developed. A platinum thin-film wire was patterned on top of a silicon chip to form a resistance temperature detector (RTD) with a nominal resistance of 1,500 Ω. A silicon dioxide layer and a thin layer of Parylene were deposited to passivate the pressure sensor diaphragm and the sensors were embedded into epoxy for protection against the caustic environment in kraft digesters. The sensors were tested up to 2 MPa and 170°C in an environment chamber. The maximum thermal error of ±1% (absolute value of ±20 kPa) full scale output (FSO) and an average sensitivity of 0.554 fF/kPa were measured. Parylene-coated silicon chips were tested for a full kraft pulping cycle with no signs of corrosion.     

Mass spectrometric immunoassay and MRM as targeted MS-based quantitative approaches in biomarker development: Potential applications to cardiovascular disease and diabetes

Type 2 diabetes mellitus (T2DM) is an important risk factor for cardiovascular disease (CVD)—the leading cause of death in the United States. Yet not all subjects with T2DM are at equal risk for CVD complications; the challenge lies in identifying those at greatest risk. Therapies directed toward treating conventional risk factors have failed to significantly reduce this residual risk in T2DM patients. Thus newer targets and markers are needed for the development and testing of novel therapies. Herein we review two complementary MS-based approaches—mass spectrometric immunoassay (MSIA) and MS/MS as MRM—for the analysis of plasma proteins and PTMs of relevance to T2DM and CVD. Together, these complementary approaches allow for high-throughput monitoring of many PTMs and the absolute quantification of proteins near the low picomolar range. In this review article, we discuss the clinical relevance of the high density lipoprotein (HDL) proteome and Apolipoprotein A-I PTMs to T2DM and CVD as well as provide illustrative MSIA and MRM data on HDL proteins from T2DM patients to provide examples of how these MS approaches can be applied to gain new insight regarding cardiovascular risk factors. Also discussed are the reproducibility, interpretation, and limitations of each technique with an emphasis on their capacities to facilitate the translation of new biomarkers into clinical practice.     

Utilizing Instructional Consultations to Enhance the Teaching Performance of Engineering Faculty

Although many kinds of data can be used to guide instructional consultations, research comparing the efficacy of such data is scant, especially in engineering. In this study, multiple modes of assessment were used to evaluate the impact of consultations informed by different kinds of data. This study illuminates two key aspects of instructional consultations: (1) their efficacy varies depending on the kind of data used to guide them, with student feedback from a Small Group Instructional Diagnosis (SGID) having the largest positive impact, and (2) the instructional consultant plays a key role in helping both interpret the available data and identify strategies for improvement. These findings suggest three implications for practice: (1) whenever possible, SGID‐based consultations should be offered systematically and proactively for engineering faculty, (2) data for other kinds of consultations should be tailored to the needs of the individual instructor, and (3) instructional consultants should be available to collaborate with faculty to enhance their teaching, thereby building an engineering culture that actively supports teaching and learning.