Investigating Current Methodologies Used in Developing Neural Network Intelligent Applications for SMEs

It has been suggested that small and medium enterprises (SMEs) are similarto large organisations. But there seems to be a sustained lack of resourcesfor implementing intelligent applications in the small business sector. Thispaper reviews methodologies for developing intelligent applications forSMEs. It also addresses the issues associated with these methodologies andproposes modalities for improvement

The triple helix of information security, government regulations and offshore outsourcing in UK

Information Security in IT, ICT, ITES sectors and associated activities is a vital solution in safeguarding tomorrow’s information society and its systems. Statistical analysis proves that only 40% of UK companies have a policy for information security in a market where only one in six companies survives without IT (ENISA, 2008). This paper explores the parameters of the conceptual triple helix model in context of the synergy among IT, ICT and ITES. Based on a study of the different models employed by UK governmental authorities, the scope of this paper is to develop a model of triple helix to be employed by the IT regulatory authority of UK. This paper evaluates statistical and conceptual data from European Network and Information Security Agency (ENISA), business models for outsourcing, activities of existing UK government authorities (and organisations) regulating best practice of information security in industry and society. Hence the hypothetical triple helix model would centralize the activities of regulatory authority. It would also facilitate change in the industry and market towards a best practice of information security without distressing the flow of existing business systems

Modelling Mobile Agent Mobility in Virtual Learning Environment (VLE) using Fitness function

This paper reports on a study conducted to ascertain the requirement for developing Virtual Learning Environments (VLEs) and how these needs are met using fitness function for modelling the solution to meet the requirements and demands of such as system. The systems used for this study was University of East London blackboard Learning System called UEL Plus. We realized that UEL Plus has multiple features to support teaching and learning. UEL Plus provides an improved communication, access to resources and advanced assessment capabilities. Our study focused fundamentally on the UEL Plus which part of VLE. The rest of the paper is organized as follows: Section 2 will describe end user categories and section 3 will highlight the mobile agents as a solution. Section 4 will introduce mobile agent fitness function and Section 5 will discusses the mobility in VLE in section 6 draws conclusion

Security strategy models (SSM)

The aim of this research paper is to analyse the individual and collective information security risks which could arise from using a security strategy model (SSM); the objective of creating the SSM was so as to protect a wireless local area network (WLAN). As such the focus of this paper shall be on the individual operational components used to create the SSM and the information security risks which stem from their being part of the SSM. In order to review the components of the SSM the paper shall use the BS ISO/IEC 17799:2005 which is the British Standard, International Standard and also the European Standard for using Information Communication Technology (ICT) correctly in order to effectively mitigate against the exposure of an organizations data to unauthorized access. The general idea of using the BS ISO/IEC 17799:2005 is so that the SSM is created based on best practice within the ICT industry of protecting confidential data or at least that the possible risks that stem from using the SSM are mitigated against; this is also known as risk based auditing. Against this backdrop the paper shall review each component of the SSM and use the risks to create a ‘Threat’ model which would then be used to create a ‘Trust model in order to strengthen the confidentiality of any data that passes through the SSM

An assessment of neural network algorithms that could aid SME survival

Artificial Neural Networks (ANNs) have been used in a wide variety of application sectors from credit card fraud detection to transportation. Over the last two decades many algorithms have been applied in the areas of classification, association, prediction and filtering of data. Such systems would allow managers of smaller businesses to determine the significance of large volumes of data quickly and just as importantly data can be classified and ordered based on the importance of the data to a predefined task for smaller businesses. Mantagno et al (2002) proposed using neural networks for identifying organisational improvement strategies. Even though Mantagno’s research focused on large organisations we believe it is imperative that smaller businesses adopt a similar approach as it could well be the deciding factor between business decline and business survival. Choy et al (2003) supports this approach in arguing that there has to be a technological searching strategy to support businesses and effective management. Although it is now possible to find many neural network models being incorporated into business applications it is still uncommon in the smaller business sector. This paper is a review of neural network algorithms applicable to SMEs

Inhibition of Neuroblastoma Tumor Growth by Targeted Delivery of MicroRNA-34a Using Anti-Disialoganglioside GD2 Coated Nanoparticles

Neuroblastoma is one of the most challenging malignancies of childhood, being associated with the highest death rate in paediatric oncology, underlining the need for novel therapeutic approaches. Typically, patients with high risk disease undergo an initial remission in response to treatment, followed by disease recurrence that has become refractory to further treatment. Here, we demonstrate the first silica nanoparticle-based targeted delivery of a tumor suppressive, pro-apoptotic microRNA, miR-34a, to neuroblastoma tumors in a murine orthotopic xenograft model. These tumors express high levels of the cell surface antigen disialoganglioside GD2 (GD(2)), providing a target for tumor-specific delivery.Nanoparticles encapsulating miR-34a and conjugated to a GD(2) antibody facilitated tumor-specific delivery following systemic administration into tumor bearing mice, resulted in significantly decreased tumor growth, increased apoptosis and a reduction in vascularisation. We further demonstrate a novel, multi-step molecular mechanism by which miR-34a leads to increased levels of the tissue inhibitor metallopeptidase 2 precursor (TIMP2) protein, accounting for the highly reduced vascularisation noted in miR-34a-treated tumors.These novel findings highlight the potential of anti-GD(2)-nanoparticle-mediated targeted delivery of miR-34a for both the treatment of GD(2)-expressing tumors, and as a basic discovery tool for elucidating biological effects of novel miRNAs on tumor growth

Development and Validation of a Risk Score for Chronic Kidney Disease in HIV Infection Using Prospective Cohort Data from the D:A:D Study

Ristola M. on työryhmien DAD Study Grp ; Royal Free Hosp Clin Cohort ; INSIGHT Study Grp ; SMART Study Grp ; ESPRIT Study Grp jäsen.Background Chronic kidney disease (CKD) is a major health issue for HIV-positive individuals, associated with increased morbidity and mortality. Development and implementation of a risk score model for CKD would allow comparison of the risks and benefits of adding potentially nephrotoxic antiretrovirals to a treatment regimen and would identify those at greatest risk of CKD. The aims of this study were to develop a simple, externally validated, and widely applicable long-term risk score model for CKD in HIV-positive individuals that can guide decision making in clinical practice. Methods and Findings A total of 17,954 HIV-positive individuals from the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study with >= 3 estimated glomerular filtration rate (eGFR) values after 1 January 2004 were included. Baseline was defined as the first eGFR > 60 ml/min/1.73 m2 after 1 January 2004; individuals with exposure to tenofovir, atazanavir, atazanavir/ritonavir, lopinavir/ritonavir, other boosted protease inhibitors before baseline were excluded. CKD was defined as confirmed (>3 mo apart) eGFR In the D:A:D study, 641 individuals developed CKD during 103,185 person-years of follow-up (PYFU; incidence 6.2/1,000 PYFU, 95% CI 5.7-6.7; median follow-up 6.1 y, range 0.3-9.1 y). Older age, intravenous drug use, hepatitis C coinfection, lower baseline eGFR, female gender, lower CD4 count nadir, hypertension, diabetes, and cardiovascular disease (CVD) predicted CKD. The adjusted incidence rate ratios of these nine categorical variables were scaled and summed to create the risk score. The median risk score at baseline was -2 (interquartile range -4 to 2). There was a 1: 393 chance of developing CKD in the next 5 y in the low risk group (risk score = 5, 505 events), respectively. Number needed to harm (NNTH) at 5 y when starting unboosted atazanavir or lopinavir/ritonavir among those with a low risk score was 1,702 (95% CI 1,166-3,367); NNTH was 202 (95% CI 159-278) and 21 (95% CI 19-23), respectively, for those with a medium and high risk score. NNTH was 739 (95% CI 506-1462), 88 (95% CI 69-121), and 9 (95% CI 8-10) for those with a low, medium, and high risk score, respectively, starting tenofovir, atazanavir/ritonavir, or another boosted protease inhibitor. The Royal Free Hospital Clinic Cohort included 2,548 individuals, of whom 94 individuals developed CKD (3.7%) during 18,376 PYFU (median follow-up 7.4 y, range 0.3-12.7 y). Of 2,013 individuals included from the SMART/ESPRIT control arms, 32 individuals developed CKD (1.6%) during 8,452 PYFU (median follow-up 4.1 y, range 0.6-8.1 y). External validation showed that the risk score predicted well in these cohorts. Limitations of this study included limited data on race and no information on proteinuria. Conclusions Both traditional and HIV-related risk factors were predictive of CKD. These factors were used to develop a risk score for CKD in HIV infection, externally validated, that has direct clinical relevance for patients and clinicians to weigh the benefits of certain antiretrovirals against the risk of CKD and to identify those at greatest risk of CKD.Peer reviewe