Total energy density as an interpretative tool

We present an unambiguous formulation for the total energy density within density-functional theory. We propose that it be used as a tool for the interpretation of computed energy and electronic structure changes during structural transformations and chemical reactions, augmenting the present use of electron density changes and changes in the Kohn-Sham local density of states and Kohn-Sham energy density.Comment: 5 pages, 3 embedded figures, submitted to J. Chem. Phy

Evaluation of Vibration Analysis to Assess Bone Mineral Density in Children

The effectiveness of vibration analysis to assess bone mineral density (BMD) in children with suspected reduction in bone density was studied. A system was designed that measured the ulna's vibration responses in vivo. The system was evaluated on the ulnae of 48 children (mean age=12.0, std=3.5 years), 31 of whom had been confirmed to have osteogenesis imperfecta (OI). All children had dual energy X-ray absorptiometry (DXA) scan as part of their routine clinical care and vibration analysis was performed on the same day. Frequency spectra of the ulnae's vibration responses were obtained and processed by principal component analysis. Four main principal components were selected and together with age, sex and right hand ulna's length were used in a regression analysis to estimate BMD. Regression analysis was repeated using the children's leave-one-out and partitioning methods. The percentage similarity and correlation between the DXA-derived and vibration analysis estimated BMDs using the leave-one-out were 80.34% and 0.59 and for partitioning were 74.2% and 0.64 respectively. There was correlation between vibration analysis BMD readings and those derived from DXA however a larger study will be needed to better establish the extent to which vibration analysis can assist in assessing bone density in clinical environments

Assessing material densities by vibration analysis and independent component analysis

The aim of this study was to investigate vibration analysis and independent component analysis (ICA) to assess the density of multiple materials making up a single structure. Density is important as it reveals information about physical properties of materials. The density of a single material can be determined from the relationship between its mass and volume. However, when a structure consists of multiple materials, identification of their individual densities from the structure is complicated. Vibration analysis is a technique that reveals information about an object’s physical properties such as its density. The investigation was carried out using a plastic test tube filled separately with three liquids of known densities; water, Chloroform and Methanol. Vibration was inducted into the tube, through an electronic system that produced a single impact at a predefined location on the tube. The resulting vibration signals were recorded using two vibration sensors placed on the tube. A signal source separation technique called ICA was used to obtain the vibration effects of the liquid and the tube. The power spectral densities (PSD) of ICA extracted vibration signals were examined. The frequency of the largest peak in the PSD was related to the liquid’s density under test. The study indicated that vibration analysis may be effective in assessing materials’ densities in a structure that contains multiple materials, however a larger study is needed to explore the findings

Analysis of the influence of trauma injury factors on the probability of survival

The probability or likelihood of survival in trauma injuries is a clinically important parameter for triage, setting treatment priorities and research and management audit. The existing methods for determining it have short comings that necessitate further development. In this study, an artificial intelligence method called fuzzy inference system (FIS) for determining the likelihood of survival in trauma injuries is being developed and evaluated. The accuracy of the FIS primarily depends on the design of its knowledge base. The required knowledge base is being designed by carrying out a detailed statistical analysis of the trauma injury profiles contained in a large data base of injury cases. As part of this analysis, the relationships between the body regions affected by trauma injuries, physiological measures (such as blood pressure, respiration rate and heart rate), age, gender , the neurological factors assessed by the Glasgow Comma Score and pre-exiting medical conditions on the probability of survival were analysed and a FIS system to indicate the likelihoods survival was proposed. The preliminary results obtained are presented

Quality of Service Evaluation and Assessment Methods in Wireless Networks

Wireless networks are capable of facilitating a reliable multimedia communication. The ease they can be deployed is ideal for disaster management. The Quality of Service (QoS) for these networks is critical to their effectiveness. Evaluation of QoS in wireless networks provides information that supports their management. QoS evaluation can be performed in multiple ways and indicates how well applications are delivered. In this work, fuzzy c-means clustering (FCM) and Kohonen unsupervised neural networks were compared for their abilities to differentiate between Good, Average and Poor QoS for voice over IP (VoIP) traffic. Fuzzy inference system (FIS), linear regression and multilayer perceptron (MLP) were evaluated to quantify QoS for VoIP. FCM and Kohonen successfully classified VoIP traffic into three types representing Low, Medium, and High QoS. FIS, regression model and MLP combined the QoS parameters (i.e. delay, jitter, and percentage packet loss ratio) with information from the generated clusters and indicated the overall QoS

Accelerometer based human joints' range of movement measurement

Accurate measurement and analysis of joints' range of movement (ROM) are important for assessing joint related health conditions and are valuable to clinicians for diagnostic and rehabilitation purposes. As an alternative to using the camera-based methods which are restrictive and expensive, and the electro-goniometers which are not sufficiently effective in some scenarios, researchers are developing the use of microelectromechanical devices such as accelerometers for measuring human joints movement. This paper presents the development of an accelerometer based system to measure movement angle, velocity, acceleration and displacement for the knee

Adaptive sampling technique using regression modelling and fuzzy inference system for network traffic

Electronic-health relies on extensive computer networks to facilitate access and to communicate various types of information in the form of data packets. To examine the effectiveness of these networks, the traffic parameters need to be analysed. Due to quantity of packets, examining their transmission parameters individually is not practical, especially when performed in real time. Sampling allows a subset of packets that accurately represents the original traffic to be chosen. In this study an adaptive sampling method based on regression and fuzzy inference system was developed. It dynamically updates the sampling by responding to the traffic changes. Its performance was found to be superior to the conventional non-adaptive sampling methods

Inertial measurement techniques for human joints' movement analysis

Abstract. Development and assessment of techniques that allow inertia measurement units consisting of an accelerometer and a gyroscope to be used for monitoring human joints' movements are presented. A new wavelet packet decomposition technique was developed that denoised the accelerometer signals. Investigations on the use of accelerometers to analyse legs’ movements are described

A recommended numbering scheme for influenza A HA subtypes.

Comparisons of residues between sub-types of influenza virus is increasingly used to assess the zoonotic potential of a circulating strain and for comparative studies across subtypes. An analysis of N-terminal cleavage sites for thirteen subtypes of influenza A hemagglutinin (HA) sequences, has previously been described by Nobusawa and colleagues. We have expanded this analysis for the eighteen known subtypes of influenza. Due to differences in the length of HA, we have included strains from multiple clades of H1 and H5, as well as strains of H5 and H7 subtypes with both high and low pathogenicity. Analysis of known structures of influenza A HA enables us to define amino acids which are structurally and functionally equivalent across all HA subtypes using a numbering system based on the mature HA sequence. We provide a list of equivalences for amino acids which are known to affect the phenotype of the virus.Funding provided by (DJS) Bill & Melinda Gates Foundation Global Health (http://www.gatesfoundation.org/) Grant # OPPGH5383, (DJS) European Union FP7 program ANTIGONE (http://cordis.europa.eu/programme/rcn/852_en.html) (278976) and (DJS) National Institute of Allergy and Infectious disease (http://www.niaid.nih.gov) Contract HHSN266200700010C. The funders had no role in the study design, data collection, analysis, decision to publish or preparation of the manuscript.This is the final published version. It originally appeared at http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0112302

Adaptive sampling for QoS traffic parameters using fuzzy system and regression model

Quality of service evaluation of wired and wireless networks for multimedia communication requires transmission parameters of packets making up the traffic through the medium to be analysed. Sampling methods play an important role in this process. Sampling provides a representative subset of the traffic thus reducing the time and resources needed for packet analysis. In an adaptive sampling, unlike fixed rate sampling, the sample rate changes over time in accordance with transmission rate or other traffic characteristics and thus could be more optimal than fixed parameter sampling. In this study an adaptive sampling technique that combined regression modelling and a fuzzy inference system was developed. The method adaptively determined the optimum number of packets to be selected by considering the changes in the traffic transmission characteristics. The method's operation was assessed using a computer network simulated in the NS-2 package. The adaptive sampling evaluated against a number of non-adaptive sampling methods gave an improved performance