Dissociation of Early And Late Face-Related Processes In Autism Spectrum Disorder And Williams Syndrome

Background: Williams syndrome (WS) and Autism Spectrum Disorders (ASD) are psychiatric conditions associated with atypical but opposite face-to-face interactions patterns: WS patients overly stare at others, ASD individuals escape eye contact. Whether these behaviors result from dissociable visual processes within the occipito-temporal pathways is unknown. Using high-density electroencephalography, multivariate signal processing algorithms and a protocol designed to identify and extract evoked activities sensitive to facial cues, we investigated how WS (N=14), ASD (N=14) and neurotypical subjects (N=14) decode the information content of a face stimulus. Results: We found two neural components in neurotypical participants, both strongest when the eye region was projected onto the subject's fovea, simulating a direct eye contact situation, and weakest over more distant regions, reaching a minimum when the focused region was outside the stimulus face. The first component peaks at 170ms, an early signal known to be implicated in low-level face features. The second is identified later, 260ms post-stimulus onset and is implicated in decoding salient face social cues.Remarkably, both components were found distinctly impaired and preserved in WS and ASD. In WS, we could weakly decode the 170ms signal based on our regressor relative to facial features, probably due to their relatively poor ability to process faces’ morphology, while the late 260ms component was highly significant. The reverse pattern was observed in ASD participants who showed neurotypical like early 170ms evoked activity but impaired late evoked 260ms signal. Conclusions: Our study reveals a dissociation between WS and ASD patients and point at different neural origins for their social impairments.

Detection and Analysis of Man-Machine Interactive Software Vulnerabilities Based on Ultrasonic Data Acquisition and Signal Processing Algorithms

With the gradual increase in the informatization, there is much software in various industries, such as data management, business execution, public orientation, and company OA, which greatly facilitates the development of various tasks, but it also brings many hidden dangers. There exist certain vulnerabilities in some software, which have become backdoors to be attacked. In view of these needs and potential hazards, the ultrasonic data acquisition and signal processing algorithms are introduced in this paper, analyzing and grasping the possibility of potentially dangerous paths by combining the instruction addresses and locations of software vulnerabilities, and avoid the existence of these software vulnerabilities through corresponding constraint instructions. The simulation experiment results prove that the ultrasonic data acquisition and signal processing algorithms are effective and can support the detection and analysis of man-machine interactive software vulnerabilities.

Теоретичні основи побудови багаточастотних радіометричних комплексів для виявлення БпЛА на тлі атмосферного випромінювання

Due to the impossibility of hiding the unmanned aerial vehicles (UAV) own radiothermal radiation or reducing its contrast against the background of atmospheric radiation, it is advisable to use highly sensitive radiometric receivers to solve the detection problem. The optimal method for complexing the results of measurements in multichannel radiometric receivers and identifying different types and classes of UAV against the sky in X, Ka, and W wave ranges under different meteorological conditions has been developed. end-to-end optimization of methods and algorithms will reveal the theoretical foundations of the construction of radiometric systems, ranging from the field of registration of electromagnetic fields to the final stages. In cloudless and clear weather, radiometric measurements in the W range will allow to obtain high-precision estimates of the spatial position of UAVs, in the X range of reliable observations in rain, snow, fog. The use of the Ka-band receiver in the radiometric complex will allow to realize the best sensitivity due to the technical achievements of domestic production in the creation of broadband radiometric receivers in this waveband. Studies of the main parameters of UAV detection have been conducted, namely, the probability of erroneous detection alarm and the probability of correct detection. The obtained theoretical results allow to determine signal processing algorithms and optimal structures of radiometric receivers, to analyze the maximum measurement error and to develop recommendations for experiments. Having received a database of radiometric contrasts, it is possible to further implement technical solutions to increase the capabilities of airspace monitoring for UAV detection. Recommendations are given for the practical choice of the UAV detection threshold to ensure the probability of correct detection is not worse than 0.9 for different angles of observation, atmospheric state, size and material of manufacture.

Spatial resolution enhancement of rotational-radar subsurface datasets using combined processing method

Effective visualisation of railway tunnel subsurface features (e.g. voids, utilities) provides critical insight into structural health and underpins planning of essential targeted predictive maintenance. Subsurface visualisation here utilises a rotating ground penetrating radar antenna system for 360° point cloud data capture. This technology has been constructed by our industry partner Railview Ltd, and requires the development of complimentary signal processing algorithms to improve feature localisation. The main novelty of this work is extension of Shrestha and Arai’s Combined Processing Method (CPM) to 360° Ground Penetrating Radar (360GPR) datasets, for first-time application in the context of railway tunnel structural health inspection. Initial experimental acquisition of a sample rotational transect for CPM enhancement is achieved by scanning a test section of tunnel sidewall - featuring predefined target geometry - with the rotating antenna. Next, frequency data separately undergo Inverse Fast Fourier Transform (IFFT) and Multiple Signal Classification (MUSIC) processing to recover temporal responses. Numerical implementation steps are explicitly provided for both MUSIC and two associated spatial smoothing algorithms, addressing an identified information deficit in the field. Described IFFT amplitude is combined with high spatial resolution of MUSIC via the CPM relation. Finally, temporal responses are compared qualitatively and quantitatively, evidencing the significant enhancement capabilities of CPM.

Nondestructive Evaluation of Electroplating-Induced Hydrogen Embrittlement in Cadmium-Coated High-Strength Steel Using Ultrasonic Surface Waves

Development of a nondestructive evaluation (NDE) method to detect nascent hydrogen embrittlement (HE) in electroplated high-strength steel parts is becoming important for the aerospace industry. This research investigates the feasibility of surface acoustic waves (SAWs) measurements to distinguish between cadmium (Cd) plated SAE 4340 steel samples with low and high HE susceptibilities. SAWs were generated with a 10 MHz piezoelectric transducer and detected by line scans via a laser Doppler vibrometer setup. Using signal processing algorithms in MATLAB, SAW velocities as well as attenuation coefficients were estimated. Depth profiles of steel hardness near coatings were also evaluated using Vickers microindentation tests. Average steel hardness in not-baked samples was slightly increased. Cd coatings were characterized by laser and optical microscopy methods. Small variations found in thickness and surface roughness of the Cd coatings among the samples did not significantly affect the NDE results. On average, samples in the not-baked condition (high HE risk) exhibited lower SAW attenuation coefficients compared to immediately baked and late-baked conditions (low HE risk). However, it was not possible to distinguish between the manufacturing conditions of individual samples due to overlaps in attenuation measurement results. SAW velocities as estimated by the cross-correlation method were found to be not sensitive to manufacturing conditions.

On the Sensing and Decoding of Phantom Motions for Control of the Cybernetics of the Upper-Limb Prosthesis

The cybernetic interface within an upper-limb prosthesis facilitates a Human–Machine interaction and ultimately control of the prosthesis limb. A coherent flow between the phantom motion and subsequent actuation of the prosthesis limb to produce the desired gesture hinges heavily upon the physiological sensing source and its ability to acquire quality signals, alongside appropriate decoding of these intent signals with the aid of appropriate signal processing algorithms. In this paper, we discuss the sensing and signal processing aspects of the overall prosthesis control cybernetics, with emphasis on transradial, transhumeral, and shoulder disarticulate amputations, which represent considerable upper-limb amputees typically encountered within the population.

Action of Finite Group Presentations on Signal Space

The use of finite group presentations in signal processing has not been exploit in the current literature. Based on the existing signal processing algorithms (not necessarily group theoretic approach), various signal processing transforms have unique decomposition capabilities, that is, different types of signal has different transformation combination. This paper aimed at studying representation of finite groups via their actions on Signal space and to use more than one transformation to process a signal within the context of group theory. The objective is achieved by using group generators as actions on Signal space which produced output signal for every corresponding input signal. It is proved that the subgroup presentations act on signal space by conjugation. Hence, a different approach to signal processing using group of transformations and presentations is established.

Geometry Monitoring of Rotating Parts of Power Unit with an Adapted Doppler Preprocessor

Current work is devoted to the development of a device for monitoring the dynamic shape of a power unit. The work is based on the FMCW method. The light source uses a low-coherence semiconductor laser diode. Signal processing is performed on an adapted Doppler processor. The paper describes the methods, hardware and signal processing algorithms.