Reviewing the current state of machine learning for artificial intelligence with regards to the use of contextual information

This paper will consider the current state of Machine Learning for Artificial Intelligence, more specifically for applications, such as: Speech Recognition, Game Playing and Image Processing. The artificial world tends to make limited use of context in comparison to what currently happens in human life, while it would benefit from improvements in this area. Additionally, the process of transferring knowledge between application domains is another important area where artificial system can improve. Using context and transferability would have several potential benefits, such as: better ability to function in multiple problem domains, improved understanding of human interaction and stronger grasping of current and potential future situations. While these items are all quite usual to us humans, it is particularly challenging to integrate them into artificial systems, as will be shown within this review. The limitations of our current systems with regards to these topics and the achievable improvements, if these items would be addressed, will also be covered. It is expected that by utilising transferability and/or context, many algorithms in the artificial intelligence field will be able to expand their functionality considerably and should provide for more general purpose learning algorithms

The benefits of contextual information for speech recognition systems

This paper demonstrates the significance of using contextual information in machine learning and speech recognition. While the benefits of contextual information in human communication are widely known, their significance is rarely explored or discussed with a view to their potential for improving speech recognition accuracy. The presented research primarily focuses on an undertaken empirical study that looks at how context affects human communication and understanding. During the study, comparisons between human communication with and without context, have shown overall recognition improvements of over 30% when contextual information is provided. The study has also investigated the importance of the former/middle/latter part of a word towards recognition. These results show that the first two-thirds of a spoken word are key for humans to correctly infer a word. The conclusions from the performed study are then drawn upon to identify useful types of context that can help a machine’s understanding, and how such contextual information can be gathered in speech recognition and machine learning systems. This paper shows that context is not only highly important for human communication, but can easily provide a wealth of information to enhance computational systems

Roflumilast in moderate-to-severe chronic obstructive pulmonary disease treated with longacting bronchodilators: two randomised clinical trials

Background Patients with chronic obstructive pulmonary disease (COPD) have few options for treatment. The efficacy and safety of the phosphodiesterase-4 inhibitor roflumilast have been investigated in studies of patients with moderate-to-severe COPD, but not in those concomitantly treated with longacting inhaled bronchodilators. The effect of roflumilast on lung function in patients with COPD that is moderate to severe who are already being treated with salmeterol or tiotropium was investigated. Methods In two double-blind, multicentre studies done in an outpatient setting, after a 4-week run-in, patients older than 40 years with moderate-to-severe COPD were randomly assigned to oral roflumilast 500 mu g or placebo once a day for 24 weeks, in addition to salmeterol (M2-127 study) or tiotropium (M2-128 study). The primary endpoint was change in prebronchodilator forced expiratory volume in 1s (FEV(1)). Analysis was by intention to treat. The studies are registered with ClinicalTrials.gov, number NCT00313209 for M2-127, and NCT00424268 for M2-128. Findings In the salmeterol plus roflumilast trial, 466 patients were assigned to and treated with roflumilast and 467 with placebo; in the tiotropium plus roflumilast trial, 371 patients were assigned to and treated with roflumilast and 372 with placebo. Compared with placebo, roflumilast consistently improved mean prebronchodilator FEV(1) by 49 mL (p<0.0001) in patients treated with salmeterol, and 80 mL (p<0.0001) in those treated with tiotropium. Similar improvement in postbronchodilator FEV(1) was noted in both groups. Furthermore, roflumilast had beneficial effects on other lung function measurements and on selected patient-reported outcomes in both groups. Nausea, diarrhoea, weight loss, and, to a lesser extent, headache were more frequent in patients in the roflumilast groups. These adverse events were associated with increased patient withdrawal. Interpretation Roflumilast improves lung function in patients with COPD treated with salmeterol or tiotropium, and could become an important treatment for these patients

Modelling of the effect of ELMs on fuel retention at the bulk W divertor of JET

Effect of ELMs on fuel retention at the bulk W target of JET ITER-Like Wall was studied with multi-scale calculations. Plasma input parameters were taken from ELMy H-mode plasma experiment. The energetic intra-ELM fuel particles get implanted and create near-surface defects up to depths of few tens of nm, which act as the main fuel trapping sites during ELMs. Clustering of implantation-induced vacancies were found to take place. The incoming flux of inter-ELM plasma particles increases the different filling levels of trapped fuel in defects. The temperature increase of the W target during the pulse increases the fuel detrapping rate. The inter-ELM fuel particle flux refills the partially emptied trapping sites and fills new sites. This leads to a competing effect on the retention and release rates of the implanted particles. At high temperatures the main retention appeared in larger vacancy clusters due to increased clustering rate

Current Research into Applications of Tomography for Fusion Diagnostics

Retrieving spatial distribution of plasma emissivity from line integrated measurements on tokamaks presents a challenging task due to ill-posedness of the tomography problem and limited number of the lines of sight. Modern methods of plasma tomography therefore implement a-priori information as well as constraints, in particular some form of penalisation of complexity. In this contribution, the current tomography methods under development (Tikhonov regularisation, Bayesian methods and neural networks) are briefly explained taking into account their potential for integration into the fusion reactor diagnostics. In particular, current development of the Minimum Fisher Regularisation method is exemplified with respect to real-time reconstruction capability, combination with spectral unfolding and other prospective tasks

Impact of ICRF on the scrape-off layer and on plasma wall interactions: From present experiments to fusion reactor

Recent achievements in studies of the effects of ICRF (Ion Cyclotron Range of Frequencies) power on the SOL (Scrape-Off Layer) and PWI (Plasma Wall Interactions) in ASDEX Upgrade (AUG), Alcator C-Mod, and JET-ILW are reviewed. Capabilities to diagnose and model the effect of DC biasing and associated impurity production at active antennas and on magnetic field connections to antennas are described. The experiments show that ICRF near-fields can lead not only to E×B convection, but also to modifications of the SOL density, which for Alcator C-Mod are limited to a narrow region near antenna. On the other hand, the SOL density distribution along with impurity sources can be tailored using local gas injection in AUG and JET-ILW with a positive effect on reduction of impurity sources. The technique of RF image current cancellation at antenna limiters was successfully applied in AUG using the 3-strap AUG antenna and extended to the 4-strap Alcator C-Mod field-aligned antenna. Multiple observations confirmed the reduction of the impact of ICRF on the SOL and on total impurity production when the ratio of the power of the central straps to the total antenna power is in the range 0.6<P$_{cen}$/P$_{total}$<0.8. Near-field calculations indicate that this fairly robust technique can be applied to the ITER ICRF antenna, enabling the mode of operation with reduced PWI. On the contrary, for the A2 antenna in JET-ILW the technique is hindered by RF sheaths excited at the antenna septum. Thus, in order to reduce the effect of ICRF power on PWI in a future fusion reactor, the antenna design has to be optimized along with design of plasmafacing components

Impact of fast ions on density peaking in JET: fluid and gyrokinetic modeling

The effect of fast ions on turbulent particle transport, driven by ion temperature gradient (ITG)/ trapped electron mode turbulence, is studied. Two neutral beam injection (NBI) heated JET discharges in different regimes are analyzed at the radial position ρ$_{t}$=0.6, one of them an L-mode and the other one an H-mode discharge. Results obtained from the computationally efficient fluid model EDWM and the gyro-fluid model TGLF are compared to linear and nonlinear gyrokinetic GENE simulations as well as the experimentally obtained density peaking. In these models, the fast ions are treated as a dynamic species with a Maxwellian background distribution. The dependence of the zero particle flux density gradient (peaking factor) on fast ion density, temperature and corresponding gradients, is investigated. The simulations show that the inclusion of a fast ion species has a stabilizing influence on the ITG mode and reduces the peaking of the main ion and electron density profiles in the absence of sources. The models mostly reproduce the experimentally obtained density peaking for the L-mode discharge whereas the H-mode density peaking is significantly underpredicted, indicating the importance of the NBI particle source for the H-mode density profile

The effect of beryllium oxide on retention in JET ITER-like wall tiles

Preliminary results investigating the microstructure, bonding and effect of beryllium oxide formation on retention in the JET ITER-like wall beryllium tiles, are presented. The tiles have been investigated by several techniques: Scanning Electron Microscopy (SEM) equipped with Energy Dispersive X-ray (EDX), Transmission Electron microscopy (TEM) equipped with EDX and Electron Energy Loss Spectroscopy (EELS), Raman Spectroscopy and Thermal Desorption Spectroscopy (TDS). This paper focuses on results from melted materials of the dump plate tiles in JET. From our results and the literature, it is concluded, beryllium can form micron deep oxide islands contrary to the nanometric oxides predicted under vacuum conditions. The deepest oxides analyzed were up to 2-micron thicknesses. The beryllium Deuteroxide (BeOxDy) bond was found with Raman Spectroscopy. Application of EELS confirmed the oxide presence and stoichiometry. Literature suggests these oxides form at temperatures greater than 700 °C where self-diffusion of beryllium ions through the surface oxide layer can occur. Further oxidation is made possible between oxygen plasma impurities and the beryllium ions now present at the wall surface. Under Ultra High Vacuum (UHV) nanometric Beryllium oxide layers are formed and passivate at room temperature. After continual cyclic heating (to the point of melt formation) in the presence of oxygen impurities from the plasma, oxide growth to the levels seen experimentally (approximately two microns) is proposed. This retention mechanism is not considered to contribute dramatically to overall retention in JET, due to low levels of melt formation. However, this mechanism, thought the result of operation environment and melt formation, could be of wider concern to ITER, dependent on wall temperatures

Modelling of tungsten erosion and deposition in the divertor of JET-ILW in comparison to experimental findings

The erosion, transport and deposition of tungsten in the outer divertor of JET-ILW has been studied for an HMode discharge with low frequency ELMs. For this specific case with an inter-ELM electron temperature at the strike point of about 20 eV, tungsten sputtering between ELMs is almost exclusively due to beryllium impurity and self-sputtering. However, during ELMs tungsten sputtering due to deuterium becomes important and even dominates. The amount of simulated local deposition of tungsten relative to the amount of sputtered tungsten in between ELMs is very high and reaches values of 99% for an electron density of 5E13 cm$^{-3}$ at the strike point and electron temperatures between 10 and 30 eV. Smaller deposition values are simulated with reduced electron density. The direction of the B-field significantly influences the local deposition and leads to a reduction if the E×B drift directs towards the scrape-off-layer. Also, the thermal force can reduce the tungsten deposition, however, an ion temperature gradient of about 0.1 eV/mm or larger is needed for a significant effect. The tungsten deposition simulated during ELMs reaches values of about 98% assuming ELM parameters according to free-streaming model. The measured WI emission profiles in between and within ELMs have been reproduced by the simulation. The contribution to the overall net tungsten erosion during ELMs is about 5 times larger than the one in between ELMs for the studied case. However, this is due to the rather low electron temperature in between ELMs, which leads to deuterium impact energies below the sputtering threshold for tungsten

Impact of fast ions on density peaking in JET : fluid and gyrokinetic modeling

The effect of fast ions on turbulent particle transport, driven by ion temperature gradient (ITG)/trapped electron mode turbulence, is studied. Two neutral beam injection (NBI) heated JET discharges in different regimes are analyzed at the radial position rho(t) = 0.6, one of them an L-mode and the other one an H-mode discharge. Results obtained from the computationally efficient fluid model EDWM and the gyro-fluid model TGLF are compared to linear and nonlinear gyrokinetic GENE simulations as well as the experimentally obtained density peaking. In these models, the fast ions are treated as a dynamic species with a Maxwellian background distribution. The dependence of the zero particle flux density gradient (peaking factor) on fast ion density, temperature and corresponding gradients, is investigated. The simulations show that the inclusion of a fast ion species has a stabilizing influence on the ITG mode and reduces the peaking of the main ion and electron density profiles in the absence of sources. The models mostly reproduce the experimentally obtained density peaking for the L-mode discharge whereas the H-mode density peaking is significantly underpredicted, indicating the importance of the NBI particle source for the H-mode density profile