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The impact of the Fourth Industrial Revolution has brought significant attention to Condition-based maintenance (CBM) for autonomous ships. This study aims to apply CBM to the fuel supply pump of a ship. Five major failures were identified through reliability analysis, and structural analysis was conducted to investigate the mechanisms by which one failure induces another, leading to the identification of three compound failure scenarios. Data were collected on a test bed under normal conditions, five single failure conditions, and three compound failure conditions. The acceleration data from the experiments were transformed into 2D arrays corresponding to a single pump rotation, and a method was proposed to compensate for the errors accumulated during the repeated array generation. The data were vectorized using a simplified CNN structure and applied to six multi-label learning methods, which were compared to identify the optimal approach. Among the six methods, the Label Powerset (LP) was found to be the most effective. Multi-label learning captures correlations between labels, similar to the failure-inducing mechanisms learned from structural analysis. [ABSTRACT FROM AUTHOR]

To improve neuromorphic computing performance, neuromorphic system components should mimic the behaviors of organic systems. In this study, a synaptic a-Si:H/a-Ga2O3 phototransistor featuring all-optical and -electrical emulation is fabricated in a manner advantageous for complementary metal-oxide-semiconductor process integration. The phototransistor exhibits excitatory and inhibitory synaptic behaviors under stimulation by both optical and electrical signals. It mimics several essential synaptic functions, including excitatory postsynaptic current, inhibitory postsynaptic current, short-term memory, long-term memory, paired-pulse facilitation, and spike-timing-dependent plasticity. The optical and electrical modulation mechanisms are confirmed to arise from the a-Si:H/a-Ga2O3 heterojunction structure and interface effects, and the device is shown to operate at low power in both optical and electrical modes. The all-optical weight modulation function is applied to the wavelength-differential behavior response of zebrafish, successfully mimicking the color perception process of the organism. Finally, to verify the translation of the optoelectrical-derived synaptic behaviors of the phototransistor into artificial neuromorphic computation, handwritten digit image recognition of the Modified National Institute of Standards and Technology dataset is performed by a convolutional neural network, with a demonstrated average learning accuracy of 98.46%. These findings verify the applicability of the synaptic a-Si:H/a-Ga2O3 phototransistor in neuromorphic computing. [ABSTRACT FROM AUTHOR]

Background This study was conducted as an effort to develop a Korean construction job exposure matrix (KoConJEM) based on 60 occupations recently consolidated by the construction workers mutual aid association for use by the construction industry. Methods The probability, intensity, and prevalence of exposure to 26 hazardous agents for 60 consolidated occupations were evaluated as binary (Yes/No) or four categories (1 to 4) by 30 industrial hygiene experts. The score for risk was calculated by multiplying the exposure intensity by the prevalence of exposure. Fleiss' kappa for each hazardous agent and occupation was used to determine agreement among the 30 experts. The JEM was expressed on a heatmap and a web-based dashboard to facilitate comparison of factors affecting exposure according to each occupation and hazardous agent. Results Awkward posture, heat/cold, heavy lifting, and noise were hazardous agents regarded as exposure is probable by at least one or more experts in all occupations, while exposure to asphalt fumes was considered hazardous in the smallest number of occupations (n = 5). Based on the degree of agreement among experts, more than half of the harmful factors and most occupations showed fair to good results. The highest risk value was 16 for awkward posture for most occupations other than safety officer. Conclusions The KoConJEM provides information on the probability, intensity, and prevalence of exposure to harmful factors, including most occupations employing construction workers; therefore, it may be useful in the conduct of epidemiological studies on assessment of health risk for construction workers. [ABSTRACT FROM AUTHOR]

In this study, the authors fabricate Sn‐doped 100‐nm thick polycrystalline β‐Ga2O3 synaptic field‐effect transistors (FETs) emulating optical and electrical spike stimulation. When stimulated by deep ultraviolet (UV) optical spikes or electric voltage spikes at the gate, the devices exhibit several essential synaptic functions of excitatory‐postsynaptic currents (EPSCs), inhibitory‐postsynaptic currents (IPSCs), paired‐pulse facilitation (PPF), spike‐number‐dependent plasticity (SNDP), and spike‐timing‐dependent plasticity (STDP). Following UV optical stimulation, the devices mimic synaptic plasticity with a photogate effect, and the gate voltage stimulation emulates the synaptic weights according to the state of the gate dielectric interface. The β‐Ga2O3 synaptic FET demonstrates synergistic functions in various optoelectronic stimulation modes and successfully mimics the visual memory formation in bees with UV photoreceptors. Moreover, to verify the translation of optoelectrical‐derived synaptic behaviors of β‐Ga2O3 synaptic FETs into artificial neuromorphic computing, handwritten digit image recognition of the Modified National Institute of Standards and Technology dataset is performed using a convolutional neural network, and a learning accuracy of 96.92% is achieved. The realization of these fundamental functions of biological synapses suggests the utility of Ga2O3‐based optoelectronic devices for next‐generation neuromorphic computing. [ABSTRACT FROM AUTHOR]