Authenticating the identity of computer users with typing biometrics and the fuzzy min-max neural network

In this paper, typing biometrics is applied as an additional security measure to the password-based or Personal Identification Number (PIN)-based systems to authenticate the identity of computer users. In particular, keystroke pressure and latency signals are analyzed using the Fuzzy Min-Max (FMM) neural network for authentication purposes. A special pressure-sensitive keyboard is designed to collect keystroke pressure signals, in addition to the latency signals, from computer users when they type their passwords. Based on the keystroke pressure and latency signals, the FMM network is employed to classify the computer users into two categories, i.e., genuine users or impostors. To assess the effectiveness of the proposed approach, two sets of experiments are conducted, and the results are compared with those from statistical methods and neural network models. The experimental outcomes positively demonstrate the potentials of using typing biometrics and the FMM network to provide an additional security layer for the current password-based or PIN-based methods in authenticating the identity of computer users.

Ensuring a proactive, evidence-based, patient safety approach to patient assessment

Aims and objectives: To argue that if all nurses were to adopt the primary survey approach (assessment of airway, breathing, circulation and disability) as the first element of patient assessment, they would be more focused on active detection of clinical deterioration rather than passive collection of patient data. Background: Nurses are the professional group that carry the highest level of responsibility for patient assessment, accurate data collection and interpretation. The timely recognition of, and response to deteriorating patients, is dependent on the measurement and interpretation of pertinent physiological data by nurses. Design: Discursive paper. Methods: Traditionally taught and commonly used approaches to patient assessment such as 'vital signs' and 'body systems' are not evidence-based nor framed in patient safety. The primary survey approach as the first element in patient assessment has three major advantages: (1) data are collected according to clinical importance; (2) data are collected using the same framework as most organisation's rapid response system activation criteria; and (3) the primary survey acts as a patient safety checklist, thereby decreasing the risk of failure to recognise, and therefore respond to, deteriorating patients. Conclusion: The vital signs and body systems approaches to patient assessment have significant limitations in identifying clinical deterioration. The primary survey approach provides nurses with a consistent, evidence-based and sequenced approach to patient assessment in every clinical setting. Relevance to clinical practice: All nurses should use a primary survey approach as the first element of patient assessment in every patient encounter as a patient safety strategy. © 2014 John Wiley & Sons Ltd.

"Cancer 2015": a prospective, population-based cancer cohort-phase 1: feasibility of genomics-guided precision medicine in the clinic

"Cancer 2015" is a longitudinal and prospective cohort. It is a phased study whose aim was to pilot recruiting 1000 patients during phase 1 to establish the feasibility of providing a population-based genomics cohort. Newly diagnosed adult patients with solid cancers, with residual tumour material for molecular genomics testing, were recruited into the cohort for the collection of a dataset containing clinical, molecular pathology, health resource use and outcomes data. 1685 patients have been recruited over almost 3 years from five hospitals. Thirty-two percent are aged between 61-70 years old, with a median age of 63 years. Diagnostic tumour samples were obtained for 90% of these patients for multiple parallel sequencing. Patients identified with somatic mutations of potentially "actionable" variants represented almost 10% of those tumours sequenced, while 42% of the cohort had no mutations identified. These genomic data were annotated with information such as cancer site, stage, morphology, treatment and patient outcomes and health resource use and cost. This cohort has delivered its main objective of establishing an upscalable genomics cohort within a clinical setting and in phase 2 aims to develop a protocol for how genomics testing can be used in real-time clinical decision-making, providing evidence on the value of precision medicine to clinical practice.

Keyword search for building service-based systems

With the fast growth of applications of service-oriented architecture (SOA) in software engineering, there has been a rapid increase in demand for building service-based systems (SBSs) by composing existing Web services. Finding appropriate component services to compose is a key step in the SBS engineering process. Existing approaches require that system engineers have detailed knowledge of SOA techniques which is often too demanding. To address this issue, we propose KS3 (Keyword Search for Service-based Systems), a novel approach that integrates and automates the system planning, service discovery and service selection operations for building SBSs based on keyword search. KS3 assists system engineers without detailed knowledge of SOA techniques in searching for component services to build SBSs by typing a few keywords that represent the tasks of the SBSs with quality constraints and optimisation goals for system quality, e.g., reliability, throughput and cost. KS3 offers a new paradigm for SBS engineering that can significantly save the time and effort during the system engineering process. We conducted large-scale experiments using a real-world Web service dataset to demonstrate the practicality, effectiveness and efficiency of KS3.