Trying to adopt systems development methodologies — a case-based exploration of business users' interests

Information systems methodologies are an important component of the IS infrastructure and a primary device for organizing systems development work. Evidence suggests that methodology adoption and use are problematic. This research seeks to generate insight into business users' interest in adoption through detailed examination of a case. A framework is developed for organizing relevant research findings. The field research methods are described and details of the case reported. The case highlights the role of business managers in methodology adoption and the influence of business pressures originating in the strategic environment. Analysis shows the organizing framework to require extension to include a more direct role for business decision makers. it is argued that previous research has obscured the legitimate concern of business with systems development methodologies. As business increasingly asserts its interest in and control over IS, it will be necessary to give greater consideration to the needs of business in the selection and adoption of methodologies.     

Towards quality requirements via animated formal specifications

Assuring a high quality requirements specification document involves both an early validation process and an increased level of participation. An approach and its supporting environment which combines the benefits of a formal system specification and its subsequent execution via a rapid prototype is reported. The environment assists in the construction, clarification, validation and visualisation of a formal specification. An illustrative case study demonstrates the consequences of assertions about system properties at this early stage of software development. Our approach involves the pragmatic combination of technical benefits of formal systems engineering based techniques with the context‐sensitive notions of increased participation of both developer and user stakeholders to move us closer towards a quality requirements specification document.     

Robust neurofuzzy rule base knowledge extraction and estimation using subspace decomposition combined with regularization and D-optimality.

A new robust neurofuzzy model construction algorithm has been introduced for the modeling of a priori unknown dynamical systems from observed finite data sets in the form of a set of fuzzy rules. Based on a Takagi-Sugeno (T-S) inference mechanism a one to one mapping between a fuzzy rule base and a model matrix feature subspace is established. This link enables rule based knowledge to be extracted from matrix subspace to enhance model transparency. In order to achieve maximized model robustness and sparsity, a new robust extended Gram-Schmidt (G-S) method has been introduced via two effective and complementary approaches of regularization and D-optimality experimental design. Model rule bases are decomposed into orthogonal subspaces, so as to enhance model transparency with the capability of interpreting the derived rule base energy level. A locally regularized orthogonal least squares algorithm, combined with a D-optimality used for subspace based rule selection, has been extended for fuzzy rule regularization and subspace based information extraction. By using a weighting for the D-optimality cost function, the entire model construction procedure becomes automatic. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.     

Dissipation of Turbulent Kinetic Energy near a Bubble Plume

Profiles of the rate of dissipation of turbulent kinetic energy were inferred from temperature microstructure measurements near a bubble plume at the center of a tank with diameter of 13.7 m and maximum depth of 8.3 m. Six sets of between 18 and 51 profiles were collected at airflow rates of 0.1–0.6 L/s, measured at atmospheric pressure, and ensemble-averaged dissipation profiles were calculated. The dissipation in all cases was between 10?8 and 10?6?m2/s3 in most of the profile, but it increased sharply near the water surface. Energy considerations are used to discuss the experimental results in terms of previous numerical models of bubble plume turbulence. Two previous numerical studies show that the turbulence dissipates between 15 and 30% of the available power. In the experiments, the fraction is less than 1% because some of the energy of the plume is used to generate waves on the water surface and the profiles used to compute the volume-averaged dissipation were relatively far from the bubble plume.     

Device-based decision-making for adaptation of three-dimensional content

The goal of this research was the creation of an adaptation mechanism for the delivery of three-dimensional content. The adaptation of content, for various network and terminal capabilities – as well as for different user preferences, is a key feature that needs to be investigated. Current state-of-the art research of the adaptation shows promising results for specific tasks and limited types of content, but is still not well-suited for massive heterogeneous environments. In this research, we present a method for transmitting adapted three-dimensional content to multiple target devices. This paper presents some theoretical and practical methods for adapting three-dimensional content, which includes shapes and animation. We also discuss practical details of the integration of our methods into MPEG-21 and MPEG-4 architectures.     

Prediction of rates of freezing, thawing or cooling in solids or arbitrary shape using the finite element method

The finite element method was formulated for the solution of three dimensional heat transfer problems in solids of arbitrary geometry with variable thermal properties. These variable properties can include latent heat effects. The accuracy of the method was tested against available analytical solutions and against experimental data for freezing of regular shapes. The method gave comparable predictions to finite difference methods for similar problems and precision was therefore more limited by the data uncertainties than by the numerical approximations inherent in the method. A simplified formulation investigated gave only slightly reduced accuracy yet much shorter computation times than the general formulation. The computer codes for both formulations are available from the authors.The flexibility of the method allows application to a wide variety of situations. For example, rates of chilling, freezing or thawing food or other solids of any shape under any type of external heat transfer environment can be predicted, heterogeneous composition can be taken into account in these predictions, and simultaneous heat and mass transfer can be considered.     

The Small Molecule GAL-201 Efficiently Detoxifies Soluble Amyloid β Oligomers: New Approach towards Oral Disease-Modifying Treatment of Alzheimer’s Disease

Soluble amyloid β (Aβ) oligomers have been shown to be highly toxic to neurons and are considered to be a major cause of the neurodegeneration underlying Alzheimer’s disease (AD). That makes soluble Aβ oligomers a promising drug target. In addition to eliminating these toxic species from the patients’ brain with antibody-based drugs, a new class of drugs is emerging, namely Aβ aggregation inhibitors or modulators, which aim to stop the formation of toxic Aβ oligomers at the source. Here, pharmacological data of the novel Aβ aggregation modulator GAL-201 are presented. This small molecule (288.34 g/mol) exhibits high binding affinity to misfolded Aβ_1-42 monomers (K_D = 2.5 ± 0.6 nM). Pharmacokinetic studies in rats using brain microdialysis are supportive of its oral bioavailability. The Aβ oligomer detoxifying potential of GAL-201 has been demonstrated by means of single cell recordings in isolated hippocampal neurons (perforated patch experiments) as well as in vitro and in vivo extracellular monitoring of long-term potentiation (LTP, in rat transverse hippocampal slices), a cellular correlate for synaptic plasticity. Upon preincubation, GAL-201 efficiently prevented the detrimental effect on LTP mediated by Aβ_1-42 oligomers. Furthermore, the potential to completely reverse an already established neurotoxic process could also be demonstrated. Of particular note in this context is the self-propagating detoxification potential of GAL-201, leading to a neutralization of Aβ oligomer toxicity even if GAL-201 has been stepwise removed from the medium (serial dilution), likely due to prion-like conformational changes in Aβ_1-42 monomer aggregates (trigger effect). The authors conclude that the data presented strongly support the further development of GAL-201 as a novel, orally available AD treatment with potentially superior clinical profile.     

Proteomic Biomarkers of the Apnea Hypopnea Index and Obstructive Sleep Apnea: Insights into the Pathophysiology of Presence,Severity, and Treatment Response

Obstructive sleep apnea (OSA), a disease associated with excessive sleepiness and increased cardiovascular risk, affects an estimated 1 billion people worldwide. The present study examined proteomic biomarkers indicative of presence, severity, and treatment response in OSA. Participants (n = 1391) of the Stanford Technology Analytics and Genomics in Sleep study had blood collected and completed an overnight polysomnography for scoring the apnea–hypopnea index (AHI). A highly multiplexed aptamer-based array (SomaScan) was used to quantify 5000 proteins in all plasma samples. Two separate intervention-based cohorts with sleep apnea (n = 41) provided samples pre- and post-continuous/positive airway pressure (CPAP/PAP). Multivariate analyses identified 84 proteins (47 positively, 37 negatively) associated with AHI after correction for multiple testing. Of the top 15 features from a machine learning classifier for AHI ≥ 15 vs. AHI < 15 (Area Under the Curve (AUC) = 0.74), 8 were significant markers of both AHI and OSA from multivariate analyses. Exploration of pre- and post-intervention analysis identified 5 of the 84 proteins to be significantly decreased following CPAP/PAP treatment, with pathways involving endothelial function, blood coagulation, and inflammatory response. The present study identified PAI-1, tPA, and sE-Selectin as key biomarkers and suggests that endothelial dysfunction and increased coagulopathy are important consequences of OSA, which may explain the association with cardiovascular disease and stroke.     

Warning: statistical benchmarking is addictive. Kicking the habit in machine learning

Algorithm performance evaluation is so entrenched in the machine learning community that one could call it an addiction. Like most addictions, it is harmful and very difficult to give up. It is harmful because it has serious limitations. Yet, we have great faith in practicing it in a ritualistic manner: we follow a fixed set of rules telling us the measure, the data sets and the statistical test to use. When we read a paper, even as reviewers, we are not sufficiently critical of results that follow these rules. Here, we will debate what are the limitations and how to best address them. This article may not cure the addiction but hopefully it will be a good first step along that road.