A Novel Semi-Automated Method of Tracking Fetal Movements

We have designed software that can â€â€™look’’ at recorded ultrasound sequences. We analyzed fifteen video sequences representing recorded ultrasound scans of nine fetuses. Our method requires a small amount of user labelled pixels for processing the first frame. These initialize GrowCut 1 , a background removal algorithm, which was used for separating the fetus from its surrounding environment (segmentation). For each subsequent frame, user input is no longer necessary as some of the pixels will inherit labels from the previously processed frame. This results in our software’s ability to track movement. Two sonographers rated the results of our computer’s â€vision’ on a scale from 1 (poor fit) to 10 (excellent fit). They assessed tracking accuracy for the entire video as well as segmentation accuracy (the ability to identify fetus from non-fetus) for every 100th processed frame. There was no appreciable deterioration in the software’s ability to track the fetus over time. I

An extended framework for evidential reasoning systems

Based on the Dempster-Shafer (D-S) theory of evidence and G. Yen's (1989), extension of the theory, the authors propose approaches to representing heuristic knowledge by evidential mapping and pooling the mass distribution in a complex frame by partitioning that frame using Shafter's partition technique. The authors have generalized Yen's model from Bayesian probability theory to the D-S theory of evidence. Based on such a generalized model, an extended framework for evidential reasoning systems is briefly specified in which a semi-graph method is used to describe the heuristic knowledge. The advantage of such a method is that it can avoid the complexity of graphs without losing the explicitness of graphs. The extended framework can be widely used to build expert systems

Prediction of Limit Cycle Oscillations Using an Implicit Aeroelastic-Harmonic Balance Method

This work proposes a extends a novel approach to compute tran sonic Limit Cycle Oscillations using high fidelity analysis. CFD based Harmonic Balance methods have proven to be efficient tools to predict periodic phenomena. This paper’s contribution is to present a methodology to determine the unknown frequency of oscillations using an implicit for- mulation of the HB method to accurately capture Limit Cycle Oscillations (LCOs); this is achieved by defining a frequency updating procedure based on a coupled CFD/CSD Harmonic Balance formulation to find the LCO condition. A pitch/plunge aerofoil and respective linear structural models is used to exercise the new method. Results show consistent agreement between the proposed and time-marching methods for both LCO amplitude and frequency.

Simulation of Oil Shale Semi-Coke Particle Cold Transportation in a Spouted Bed Using CPFD Method

The spouted bed was widely used due to its good mixing of particles and effective phase transferability between the gas and solid phase. In this paper, the transportation process of particles in a 3D spouted bed was studied using the Computational Particle Fluid Dynamics (CPFD) numerical method. Experiments were conducted to verify the validity of the simulation results. Distributions of the pressure, velocities and particle concentration of transportation devices were investigated. The motion state and characteristics of multiphase flows in the transportation device were demonstrated under various operating conditions. The results showed that a good consistency was obtained between the simulated results and the experimental results. The motion characteristics of the gas-solid two-phase flow in the device was effectively predicted, which could assist the optimal operating condition estimation for the spouted transportation process.

Numerical Method for Cost-Weight Optimisation of Stringer-Skin Panels

The need to integrate cost into the early product definition process as an engineering parameter is addressed. The application studied is a fuselage panel that is typical for commercial transport regional jets. Consequently, a semi-empirical numerical analysis using reference data was coupled to model the structural integrity of thin-walled structures with regard to material failure and buckling: skin, stringer, flexural, and interrivet. The optimization process focuses on direct operating cost (DOC) as a function of acquisition cost and fuel burn. It was found that the ratio of acquisition cost to fuel burn was typically 4:3 and that there was a 10% improvement in the DOC for the minimal DOC condition over the minimal weight condition because of the manufacturing cost saving from having a reduced number of larger-area stringers and a slightly thicker skin than that preferred by the minimal weight condition. Also note that the minimal manufacturing cost condition was slightly better than the minimal weight condition, which highlights the key finding: The traditional minimal weight condition is a dated and suboptimal approach to airframe structural design.

HOS-Based Semi-Blind Spatial Equalization for MIMO Rayleigh Fading Channels

In this paper we concentrate on the direct semi-blind spatial equalizer design for MIMO systems with Rayleigh fading channels. Our aim is to develop an algorithm which can outperform the classical training based method with the same training information used, and avoid the problems of low convergence speed and local minima due to pure blind methods. A general semi-blind cost function is first constructed which incorporates both the training information from the known data and some kind of higher order statistics (HOS) from the unknown sequence. Then, based on the developed cost function, we propose two semi-blind iterative and adaptive algorithms to find the desired spatial equalizer. To further improve the performance and convergence speed of the proposed adaptive method, we propose a technique to find the optimal choice of step size. Simulation results demonstrate the performance of the proposed algorithms and comparable schemes.

A new method of measuring plastic limit of fine materials

Index properties such as the liquid limit and plastic limit are widely used to evaluate certain geotechnical parameters of fine-grained soils. Measurement of the liquid limit is a mechanical process, and the possibility of errors occurring during measurement is not significant. However, this is not the case for plastic limit testing, despite the fact that the current method of measurement is embraced by many standards around the world. The method in question relies on a fairly crude procedure known widely as the ‘thread rolling' test, though it has been the subject of much criticism in recent years. It is essential that a new, more reliable method of measuring the plastic limit is developed using a mechanical process that is both consistent and easily reproducible. The work reported in this paper concerns the development of a new device to measure the plastic limit, based on the existing falling cone apparatus. The force required for the test is equivalent to the application of a 54 N fast-static load acting on the existing cone used in liquid limit measurements. The test is complete when the relevant water content of the soil specimen allows the cone to achieve a penetration of 20 mm. The new technique was used to measure the plastic limit of 16 different clays from around the world. The plastic limit measured using the new method identified reasonably well the water content at which the soil phase changes from the plastic to the semi-solid state. Further evaluation was undertaken by conducting plastic limit tests using the new method on selected samples and comparing the results with values reported by local site investigation laboratories. Again, reasonable agreement was found.

Numerical simulation of a patent technology for sealing of deep-sea oil wells using nonlinear finite element method

For over 50 years bridge plugs and cement have been used for well abandonment and work over and are still the material of choice. However the failures of cement abandonments using bridge plugs has been reported on many occasions, some of which have resulted in fatal consequences. A new patented product is designed to address the shortcomings associated with using bridge plugs and cement. The new developed tools use an alloy based on bismuth that is melted in situ using Thermite reaction. The tool uses the expansion properties of bismuth to seal the well. Testing the new technology in real field under more than 2 km deep sea water can be expensive. Virtual simulation of the new device under simulated thermal and mechanical environment can be achieved using nonlinear finite element method to validate the product and reduce cost. Experimental testing in the lab is performed to measure heat generated due to thermite reaction. Then, a sequential thermal mechanical explicit/implicit finite element solver is used to simulate the device under both testing lab and deep water conditions.

Cognitive biases and addiction: an evolution in theory and method

An evolution in theoretical models and methodological paradigms for investigating cognitive biases in the addictions is discussed. Anomalies in traditional cognitive perspectives, and problems with the self-report methods which underpin them, are highlighted. An emergent body of cognitive research, contextualized within the principles and paradigms of cognitive neuropsychology rather than social learning theory, is presented which, it is argued, addresses these anomalies and problems. Evidence is presented that biases in the processing of addiction-related stimuli, and in the network of propositions which motivate addictive behaviours, occur at automatic, implicit and pre-conscious levels of awareness. It is suggested that methods which assess such implicit cognitive biases (e.g. Stroop, memory, priming and reaction-time paradigms) yield findings which have better predictive utility for ongoing behaviour than those biases determined by self-report methods of introspection. The potential utility of these findings for understanding "loss of control" phenomena, and the desynchrony between reported beliefs and intentions and ongoing addictive behaviours, is discussed. Applications to the practice of cognitive therapy are considered.

Multi-detection method for five common microalgal toxins based on the use of microspheres coupled to a flow-cytometry system

Freshwater and brackish microalgal toxins, such as microcystins, cylindrospermopsins, paralytic toxins, anatoxins or other neurotoxins are produced during the overgrowth of certain phytoplankton and benthic cyanobacteria, which includes either prokaryotic or eukaryotic microalgae. Although, further studies are necessary to define the biological role of these toxins, at least some of them are known to be poisonous to humans and wildlife due to their occurrence in these aquatic systems. The World Health Organization (WHO) has established as provisional recommended limit 1 μg of microcystin-LR per liter of drinking water. In this work we present a microsphere-based multi-detection method for five classes of freshwater and brackish toxins: microcystin-LR (MC-LR), cylindrospermopsin (CYN), anatoxin-a (ANA-a), saxitoxin (STX) and domoic acid (DA). Five inhibition assays were developed using different binding proteins and microsphere classes coupled to a flow-cytometry Luminex system. Then, assays were combined in one method for the simultaneous detection of the toxins. The IC₅₀'s using this method were 1.9 ± 0.1 μg L⁻¹ MC-LR, 1.3 ± 0.1 μg L⁻¹ CYN, 61 ± 4 μg L⁻¹ ANA-a, 5.4 ± 0.4 μg L⁻¹ STX and 4.9 ± 0.9 μg L⁻¹ DA. Lyophilized cyanobacterial culture samples were extracted using a simple procedure and analyzed by the Luminex method and by UPLC–IT-TOF-MS. Similar quantification was obtained by both methods for all toxins except for ANA-a, whereby the estimated content was lower when using UPLC–IT-TOF-MS. Therefore, this newly developed multiplexed detection method provides a rapid, simple, semi-quantitative screening tool for the simultaneous detection of five environmentally important freshwater and brackish toxins, in buffer and cyanobacterial extracts.

Belief Updating and Learning in Semi-Qualitative Probabilistic Networks

This paper explores semi-qualitative probabilistic networks (SQPNs) that combine numeric and qualitative information. We first show that exact inferences with SQPNs are NPPP-Complete. We then show that existing qualitative relations in SQPNs (plus probabilistic logic and imprecise assessments) can be dealt effectively through multilinear programming. We then discuss learning: we consider a maximum likelihood method that generates point estimates given a SQPN and empirical data, and we describe a Bayesian-minded method that employs the Imprecise Dirichlet Model to generate set-valued estimates.

Clustering-Based Ensemble Method as an Alternative to Stacking

One of the most popular techniques of generating classifier ensembles is known as stacking which is based on a meta-learning approach. In this paper, we introduce an alternative method to stacking which is based on cluster analysis. Similar to stacking, instances from a validation set are initially classified by all base classifiers. The output of each classifier is subsequently considered as a new attribute of the instance. Following this, a validation set is divided into clusters according to the new attributes and a small subset of the original attributes of the instances. For each cluster, we find its centroid and calculate its class label. The collection of centroids is considered as a meta-classifier. Experimental results show that the new method outperformed all benchmark methods, namely Majority Voting, Stacking J48, Stacking LR, AdaBoost J48, and Random Forest, in 12 out of 22 data sets. The proposed method has two advantageous properties: it is very robust to relatively small training sets and it can be applied in semi-supervised learning problems. We provide a theoretical investigation regarding the proposed method. This demonstrates that for the method to be successful, the base classifiers applied in the ensemble should have greater than 50% accuracy levels.