A case study of SME web application development effectiveness via agile methods

Abstract: The development of Web applications is an important focus of the modern information enabled organization – whether the Web application development is in-house, outsourced, or purchased as ‘commercial-off-the-shelf’ (COTS) software. Traditionally Web application development has been delivered via the dominant waterfall system. The waterfall system relies upon well-defined governance structures, linear phases, gating, and extensive reporting and sign-off documentation. An increasing number of development stakeholders criticise the waterfall system for web application development. The criticisms include a disproportionate focus on governance and process at the direct expense of flexibility and, most importantly, reduced productivity. One consequence of these criticisms is the increasing adoption of Web application development via agile-system methods. This agile-system approach centres upon smaller design teams, fewer development phases, and shorter development time tables

Intersection of inflammation and herbal medicine in the treatment of osteoarthritis

Herbal remedies and dietary supplements have become an important area of research and clinical practice in orthopaedics and rheumatology. Understanding the risks and benefits of using herbal medicines in the treatment of arthritis, rheumatic diseases, and musculoskeletal complaints is a key priority of physicians and their patients. This review discusses the latest advances in the use of herbal medicines for treating osteoarthritis (OA) by focusing on the most significant trends and developments. This paper sets the scene by providing a brief introduction to ethnopharmacology, Ayurvedic medicine, and nutrigenomics before discussing the scientific and mechanistic rationale for targeting inflammatory signalling pathways in OA by use of herbal medicines. Special attention is drawn to the conceptual and practical difficulties associated with translating data from in-vitro experiments to in-vivo studies. Issues relating to the low bioavailability of active ingredients in herbal medicines are discussed, as also is the need for large-scale, randomized clinical trial

Social cohesion and the notion of 'suspect communities': A study of the experiences and impacts of being 'suspect' for Irish communities and Muslim communities in Britain

In this article, we consider how the practice of conceiving of groups within civil society as 'communities' meshes with conceptualisations of certain populations as 'suspect' and consider some of the impacts and consequences of this for particular populations and for social cohesion. We examine how Irish and Muslim people in Britain have become aware of and have experienced themselves to be members of 'suspect communities' in relation to political violence and counterterrorism policies from 1974 to 2007 and investigate the impacts of these experiences on their everyday lives. The study focuses on two eras of political violence. The first coincides with the Irish Republican Army's (IRA) bombing campaigns in England between 1973 and 1996, when the perpetrators were perceived as 'Irish terrorists'; and the second since 2001, when, in Britain and elsewhere, the main threat of political violence has been portrayed as stemming from people who are assumed to be motivated by extreme interpretations of Islam and are often labelled as 'Islamic terrorists'. We outline why the concept of 'suspect communities' continues to be analytically useful for examining: the impact of 'bounded communities' on community cohesion policies; the development of traumatogenic environments and their ramifications; and for examining how lessons might be learnt from one era of political violence to another, especially as regards the negative impacts of practices of suspectification on Irish communities and Muslim communities. The research methods included discussion groups involving Irish and Muslim people. These demonstrated that with the removal of discourses of suspicion the common ground of Britain's urban multiculture was a sufficient basis for sympathetic exchanges. © 2012 Taylor and Francis Group, LLC

Agile software development practices in Egypt SMEs : a grounded theory investigation

Agile information system development methods have been adopted by most software development organizations due to their proven benefits in terms of flexibility, reliability, and responsiveness. However, companies face significant challenges in adopting these approaches. Specifically, this research investigates challenges faced by software development companies in Egypt while transitioning to Agile. As little previous research is available targeting their concerns, we have conducted a grounded theory investigation. Key problem areas were found including lack of cadence in sprints planning, inadequate use of effort estimation and product quality issues. The developed grounded theory reflects on the key problem areas found with SMEs adopting agile practices and can be used by software development practitioners adopting agile methods in Egypt or similar developing countries as an outline for the common problem areas they are expected to find

Lesional-targeting of neuroprotection to the inflammatory penumbra in experimental multiple sclerosis

The authors would like to thank the support of the National Multiple Sclerosis Society (USA) and the Multiple Sclerosis Society of Great Britain and Northern Ireland

Analysis of mass spectrometry data from the secretome of an explant model of articular cartilage exposed to pro-inflammatory and anti-inflammatory stimuli using machine learning

Background: Osteoarthritis (OA) is an inflammatory disease of synovial joints involving the loss and degeneration of articular cartilage. The gold standard for evaluating cartilage loss in OA is the measurement of joint space width on standard radiographs. However, in most cases the diagnosis is made well after the onset of the disease, when the symptoms are well established. Identification of early biomarkers of OA can facilitate earlier diagnosis, improve disease monitoring and predict responses to therapeutic interventions. Methods: This study describes the bioinformatic analysis of data generated from high throughput proteomics for identification of potential biomarkers of OA. The mass spectrometry data was generated using a canine explant model of articular cartilage treated with the pro-inflammatory cytokine interleukin 1 β (IL-1β). The bioinformatics analysis involved the application of machine learning and network analysis to the proteomic mass spectrometry data. A rule based machine learning technique, BioHEL, was used to create a model that classified the samples into their relevant treatment groups by identifying those proteins that separated samples into their respective groups. The proteins identified were considered to be potential biomarkers. Protein networks were also generated; from these networks, proteins pivotal to the classification were identified. Results: BioHEL correctly classified eighteen out of twenty-three samples, giving a classification accuracy of 78.3% for the dataset. The dataset included the four classes of control, IL-1β, carprofen, and IL-1β and carprofen together. This exceeded the other machine learners that were used for a comparison, on the same dataset, with the exception of another rule-based method, JRip, which performed equally well. The proteins that were most frequently used in rules generated by BioHEL were found to include a number of relevant proteins including matrix metalloproteinase 3, interleukin 8 and matrix gla protein. Conclusions: Using this protocol, combining an in vitro model of OA with bioinformatics analysis, a number of relevant extracellular matrix proteins were identified, thereby supporting the application of these bioinformatics tools for analysis of proteomic data from in vitro models of cartilage degradation

Auditing the data confidentiality of wireless local area networks

Wireless Local Area Networks (WLANs) provide many significant advantages to the contemporary business enterprise. WLANs also provide considerable security challenges for network administrators and users. Data confidentiality breaches (ie, unauthorized access to data) are the major security vulnerability within WLANs. To date, the major IT security standards from the International Standards Organisation (the ISO/IEC 17799) and the National Institute of Science and Technology (the Special Publication or SP suite) have only a superficial coverage of WLAN security controls and compliance certification strategies. The clear responsibility for WLAN managers is to provide network users with best practice security strategies to mitigate the real risk of unauthorized data access. The clear responsibility for IT auditors is to ensure that best practice security practices are in place and that operational compliance is consistently achieved. This paper describes a newly researched software auditing artifact for the evaluation of the data confidentiality levels of WLAN transmissions – and therefore by extension for the evaluation of existing security controls to mitigate the risk of WLAN confidentiality breaches. The paper describes how the software auditing artifact has been evolved via a design science research methodology, and pivots upon the real time passive sampling of data packets as they are transmitted between mobile users and mobile transmission access points. The paper describes how the software auditing artifact uses these sampled data packets to produce a very detailed evaluation of the levels of data confidentiality in effect across the WLAN. This detailed evaluation includes specific identification (for network managers) of the types of software services operating across the WLAN that are not supported with the appropriate data confidentiality controls. The paper concludes by presenting an analysis of the results achieved during beta testing of the auditing artifact within a university production WLAN environment

Do serum biomarkers really measure breast cancer?

Background Because screening mammography for breast cancer is less effective for premenopausal women, we investigated the feasibility of a diagnostic blood test using serum proteins. Methods This study used a set of 98 serum proteins and chose diagnostically relevant subsets via various feature-selection techniques. Because of significant noise in the data set, we applied iterated Bayesian model averaging to account for model selection uncertainty and to improve generalization performance. We assessed generalization performance using leave-one-out cross-validation (LOOCV) and receiver operating characteristic (ROC) curve analysis. Results The classifiers were able to distinguish normal tissue from breast cancer with a classification performance of AUC = 0.82 ± 0.04 with the proteins MIF, MMP-9, and MPO. The classifiers distinguished normal tissue from benign lesions similarly at AUC = 0.80 ± 0.05. However, the serum proteins of benign and malignant lesions were indistinguishable (AUC = 0.55 ± 0.06). The classification tasks of normal vs. cancer and normal vs. benign selected the same top feature: MIF, which suggests that the biomarkers indicated inflammatory response rather than cancer. Conclusion Overall, the selected serum proteins showed moderate ability for detecting lesions. However, they are probably more indicative of secondary effects such as inflammation rather than specific for malignancy.United States. Dept. of Defense. Breast Cancer Research Program (Grant No. W81XWH-05-1-0292)National Institutes of Health (U.S.) (R01 CA-112437-01)National Institutes of Health (U.S.) (NIH CA 84955