Contrast Adaptation in Face Perception Revealed Through EEG and Behavior

Exposure to a face can produce biases in the perception of subsequent faces. Typically, these face aftereffects are studied by adapting to an individual face or category (e.g., faces of a given gender) and can result in renormalization of perceptions such that the adapting face appears more neutral. These shifts are analogous to chromatic adaptation, where a renormalization for the average adapting color occurs. However, in color vision, adaptation can also adjust to the variance or range of colors in the distribution. We examined whether this variance or contrast adaptation also occurs for faces, using an objective EEG measure to assess response changes following adaptation. An average female face was contracted or expanded along the horizontal or vertical axis to form four images. Observers viewed a 20 s sequence of the four images presented in a fixed order at a rate of 6 Hz, while responses to the faces were recorded with EEG. A 6 Hz signal was observed over right occipito-temporal channels, indicating symmetric responses to the four images. This test sequence was repeated after 20 s adaptation to alternations between two of the faces (e.g., horizontal contracted and expanded). This adaptation resulted in an additional signal at 3 Hz, consistent with asymmetric responses to adapted and non-adapted test faces. Adapting pairs have the same mean (undistorted) as the test sequence and thus should not bias responses driven only by the mean. Instead, the results are consistent with selective adaptation to the distortion axis. A 3 Hz signal was also observed after adapting to face pairs selected to induce a mean bias (e.g., expanded vertical and expanded horizontal), and this signal was not significantly different from that observed following adaption to a single image that did not form part of the test sequence (e.g., a single image expanded both vertically and horizontally). In a further experiment, we found that this variance adaptation can also be observed behaviorally. Our results suggest that adaptation calibrates face perception not only for the average characteristics of the faces we experience but also for the gamut of faces to which we are exposed.

Impact of normalization, standardization and pre-fit on the success rate of fitting in electrochemical impedance spectroscopy

Fitting the data of an electrochemical impedance spectroscopy (EIS) typically requires manual estimation of the initial values before regression algorithms such as complex nonlinear least squares (CNLS) can be applied. This makes the success rate of the fitting dependent on the user input. Furthermore, the Randles circuit consists of parameters with substantially differing magnitudes (e.g. capacitors and resistors), which can also strongly affect the success rate of the fitting due to numerical effects. The aim of this work is to investigate methods addressing the described limitations of fitting. Therefore, a Python implementation performing a fit for EIS is benchmarked with an equivalent open source library. The examined implementation optionally includes the normalization of the parameter values, the standardization of the impedances and a pre-fit. Applying the same equivalent circuit without additional signal processing steps and with fixed initial values defined by midpoints of the value ranges, both implementations were able to fit 46.50% of the simulated database with different spectra. Applying the normalization of the parameter values (76.25%) or the same method with additional pre-fit (97.75%) lead to a significant improvement of the success rate. The standardization of impedances did not affect the success rate.

Automated Defect Detection Using Threshold Value Classification Based on Thermographic Inspection

Active infrared thermography is an attractive and reliable technique used for the non-destructive evaluation of various materials and structures, because it enables non-contact, large area, high-speed, quantitative, and qualitative inspection. However, the defect detectability is significantly deteriorated due to the excitation of a non-uniform heat source and surrounding environmental noise, requiring additional signal processing and image characterization. The lock-in infrared thermography technique has been proven to be an effective method for quantitative evaluation by extracting amplitude and phase images from a 2D thermal sequence, but it still involves a lot of noise, providing difficulties in detection. Therefore, this study explored the possibility of improving the signal-to-noise ratio by applying filtering to a stainless-steel plate with circular defects. Thereafter, automated defect detection was performed based on the threshold value through the binary images. In addition, a comparative analysis was performed to evaluate the detectability according to the presence or absence of a filtering application.

Convolutional Neural Network Design for Improvement of Machining Quality Monitoring

Automatically monitoring finishing quality by computers can achieve efficient product quality management and can improve overall production efficiency. To be able to offer quantitative measures and to achieve this goal, this paper discusses and suggests the utilization of artificial intelligence (AI) technology to predict product finishing quality by use of signals such as vibrations captured by accelerometers generated during manufacturing. To reduce the cost of inspecting products one by one, a deep one-dimensional convolutional neural network (CNN) is proposed to predict machined surface quality. In this method, dense residual skip-connections are used to improve the complexity of the model to improve the accuracy of predicted values. With the adaptation of the pooling layer in the proposed model, it is observed that the number of parameters used in the model is greatly reduced. Not only the predicted accuracy is optimized with the proposed model, the parameters that need to be stored and the computation resource that is consumed in the inference stage are significantly reduced as well. Compared with methods reported in the literature, through calibrated experimental verifications, the proposed model used in this work can improve the prediction accuracy by 10 percent, without any additional signal preprocessing efforts. The work presented in this paper is thought to have engineering implications in quantifying machining quality in the machine tools industry.

Methods and results of effective application of modern infra-red imaging technologies for measuring hydrophysical processes

Object and purpose of research. The paper presents characteristics of modern infra-red imaging technologies and highlights their potential for wide application. Materials and methods. Investigations are presented based on the account of balance of various components of water surface thermal radiation and its changes under different conditions of water surface observations, measurements at different sky radiation intensities and application of additional natural illumination by solar radiation. Main results. Modern infra-red imaging technologies are analyzed for convenience of measurements using operator’s windows, different spectral IR ranges, various matrix receiver formats as well as comparative temperature fields presentation using 3-D control points, lines, etc. Comparative measurements of various instruments are given in recording of natural and artificial anomalies of thermal radiation related to changes of the air/water thermal interface and similar measurements with prevailing reflected thermal radiation component. Possibility of applying IR imaging technologies with additional signal amplification by simultaneous recording of reflected solar radiation are considered. Data recorded concurrently in visible and IR ranges of spectrum are compared. Conclusion. Conclusions are given regarding various measuring methods to record the proper thermal radiation of water surface and its reflected component, which can be used to measure the wave structure of marine surface. The possibilities of visible online analysis and structured analysis of the recorded temperature field with simultaneous display of its temperature, color, linear and time scale are demonstrated.

The effect of the nature of the сhalcogen atom on the extraction and adsorption characteristics of chalcogen-containing oligomers based on chlorex

The extraction and adsorption characteristics of chalcogen-containing oligomers derived from chlorex and elemental chalcogens in the hydrazine hydrate–base systems were studied. Sulphur- and selenium-containing oligomers synthesised in hydrazine hydrate–monoethanolamine systems are soluble in organic solvents. The as-obtained solutions are capable of extracting the following ions from water solutions: Hg2+, Cd2+, Zn2+, Pb2+, Cu2+ and Ni2+. Oligomers synthesised in the hydrazine hydrate–water–KOH system (sulphur- and selenium-containing oligomers) and a tellurium-containing oligomer obtained in the hydrazine hydrate–KOH system were used as adsorbents. It was assumed that the extraction and adsorption of metal ions by chalcogen-containing oligomers is carried out through the formation of complexes in which the chalcogen atoms act as ligands. The effect of the nature of chalcogen atoms on the possibility of forming complexes, i.e. on the extraction and adsorption properties of the oligomers used, was considered using the theory of hard and soft acids and bases (HSAB). According to this theory, the cations Hg2+ and Cd2+ belong to soft acids, while the cations Zn2+, Pb2+, Cu2+ and Ni2+ belong to acids of intermediate hardness. Chalcogen atoms are classified as soft bases. The conducted experiment showed that Hg2+ and Cd2+ ions are easily extracted and adsorbed by all the oligomers used, while the intermediate-hardness cations most easily interact with the sulphur-containing oligomers. The formation of oligomer–metal complexes was confirmed by analysing IR and 77Se NMR spectra recorded for sulphur- and selenium-containing oligomers before and after the extraction. The recorded IR spectra contained obvious changes in the nature of the absorption bands due to the stretching vibrations of the C–S and C–Se bonds. An additional signal of de-screened selenium nuclei was observed in the 77Se NMR spectrum. An insignificant change in the nature of the IR spectra in the region of stretching C–O vibrations indicated a weak participation of oxygen in the formation of complexes. It can be assumed that the role of oxygen in maintaining the high rates of extraction and adsorption is associated with an increase in the flexibility of macromolecules, which ensures a more favourable geometry for complex formation.

Design of Velocity PID-Fuzzy Power System Stabilizer Using Particle Swarm Optimization

Power system stabilizer (PSS) is used to damping power system local and interarea modes of oscillation. It will act as additional signal through the generator excitation system which produces a component of electrical torque in phase with speed variation. Fuzzy controller is nonlinear. It is more difficult to set the fuzzy controller gains compared to conventional PID controller. This research proposed velocity (PID-FPSS) its gains are tuned off-line by particle swarm optimization techniques (PSO). The objectives are to damp local-area mode of oscillations that occur following power system disturbances. The effectiveness of the proposed technique is illustrated by applying the velocity PID-FPSS to a single-machine infinite bus power system that is typically used in the literature to test the performance of power system stabilizers. The simulation studies has been tested in MATLAB SIMULINK package . A comparison between the proposed PID-FPSS and a well-tuned and designed robust power system stabilizer (RPSS) confirms the superiority of the PID-FPSS.

Hippocampal Involvement With Vigabatrin-Related MRI Signal Abnormalities in Patients With Infantile Spasms: A Novel Finding

Background: In a subset of infants exhibiting typical vigabatrin-related magnetic resonance imaging (MRI) changes, the authors observed additional hippocampal signal abnormalities. The authors investigated occurrence and significance of additional signal abnormalities. Methods: A retrospective review of infantile spasms patients with typical vigabatrin-related MRI abnormalities was performed. Atypical features included signal changes unilaterally or at previously unreported sites. Comparisons were made between patients with and without atypical features. Results In all, 26/55 (47%) exhibited typical vigabatrin-related MRI changes, with additional signal abnormalities in the hippocampi in 6 of 26. On follow-up, evolution of hippocampal signal changes paralleled changes at typical locations in 4 patients. Two patients, clinically well, without follow-up MRI. Patients with and without additional hippocampal signal changes did not differ with respect to clinical factors, including seizure status. One patient had unilateral thalamic/cerebral peduncle signal abnormality along with typical vigabatrin changes. Conclusions: Hippocampal changes seen in subset of patients with typical vigabatrin-related changes may be attributable to vigabatrin exposure in the appropriate circumstance.