Search Results (6)

A conventional microchannel plate framing camera is typically utilized for inertial confinement fusion diagnosis. However, as a vacuum electronic device, it has inherent limitations, such as a complex structure and the inability to achieve single-line-of-sight imaging. To address these challenges, a CMOS image sensor that can be seamlessly integrated with an electronic pulse broadening system can provide a viable alternative to the microchannel plate detector. This paper introduces the design of an 8 × 8 pixel-array ultrashort shutter-time single-framing CMOS image sensor, which leverages silicon epitaxial processing and a 0.18 μm standard CMOS process. The focus of this study is on the photodiode and the readout pixel-array circuit. The photodiode, designed using the silicon epitaxial process, achieves a quantum efficiency exceeding 30% in the visible light band at a bias voltage of 1.8 V, with a temporal resolution greater than 200 ps for visible light. The readout pixel-array circuit, which is based on the 0.18 μm standard CMOS process, incorporates 5T structure pixel units, voltage-controlled delayers, clock trees, and row-column decoding and scanning circuits. Simulations of the pixel circuit demonstrate an optimal temporal resolution of 60 ps. Under the shutter condition with the best temporal resolution, the maximum output swing of the pixel circuit is 448 mV, and the output noise is 77.47 μV, resulting in a dynamic range of 75.2 dB for the pixel circuit; the small-signal responsivity is 1.93 × 10⁻⁷ V/e⁻, and the full-well capacity is 2.3 Me⁻. The maximum power consumption of the 8 × 8 pixel-array and its control circuits is 0.35 mW. Considering both the photodiode and the pixel circuit, the proposed CMOS image sensor achieves a temporal resolution better than 209 ps. Full article

In this paper, we address the problem of dynamic scheduling of a multipurpose batch process subject to two types of disturbances, namely, processing time variation and demand uncertainty. We propose a rescheduling strategy that combines several ideas. First, when we generate a new schedule, we simultaneously construct a Directed Acyclic Graph (DAG) to represent this new schedule. While each node in the DAG represents an operation, each arc represents the dependency of an operation on another. Based on this DAG, we then use a simple procedure to determine how long an operation is allowed to be delayed without affecting the current makespan. After that, when the new schedule is used for online execution, we trigger a rescheduling procedure only when (1) we infer from the predetermined delayable time information that the current makespan will be extended, or (2) we observe new demands, or (3) the current schedule is not guaranteed to be feasible. In the rescheduling procedure, only the affected operations are allowed to be revised, while those unaffected operations are fixed. By doing this, we can reduce system nervousness and improve computational efficiency. The computational results demonstrate that our method can achieve an order of magnitude of reduction in both the number of operation changes and the computational time with a slightly better long-term makespan, compared to the widely used periodically–completely rescheduling strategy. Full article

In this paper, we utilise optimization methods to determine a frequency-independent phase shift such that two phase-shifted versions of a signal can be summed and the resulting amplitude spectrum is unchanged. A phase difference between two signals is thus defined, which remains constant for all frequencies within a given range. For the intended purpose of this study, we set the frequency range to the audible human hearing range of 16 Hz–20 kHz. We found that a new 3-stage filter method provides a variable phase shifter (i.e., ϕ = 0–360°) without the need for additional amplifiers. In addition, we present a new method that reduces the number of filters necessary, improving both the accuracy and efficiency of current techniques. Full article

Recurrent Neural Networks (RNNs) are applied in safety-critical fields such as autonomous driving, aircraft collision detection, and smart credit. They are highly susceptible to input perturbations, but little research on RNN-oriented testing techniques has been conducted, leaving a threat to a large number of sequential application domains. To address these gaps, improve the test adequacy of RNNs, find more defects, and improve the performance of RNNs models and their robustness to input perturbations. We aim to propose a test coverage metric for the underlying structure of RNNs, which is used to guide the generation of test inputs to test RNNs. Although coverage metrics have been proposed for RNNs, such as the hidden state coverage in RNN-Test, they ignore the fact that the underlying structure of RNNs is still a fully connected neural network but with an additional “delayer” that records the network state at the time of data input. We use the contributions, i.e., the combination of the outputs of neurons and the weights they emit, as the minimum computational unit of RNNs to explore the finer-grained logical structure inside the recurrent cells. Compared to existing coverage metrics, our research covers the decision mechanism of RNNs in more detail and is more likely to generate more adversarial samples and discover more flaws in the model. In this paper, we redefine the contribution coverage metric applicable to Stacked LSTMs and Stacked GRUs by considering the joint effect of neurons and weights in the underlying structure of the neural network. We propose a new coverage metric, RNNCon, which can be used to guide the generation of adversarial test inputs. And we design and implement a test framework prototype RNNCon-Test. 2 datasets, 4 LSTM models, and 4 GRU models are used to verify the effectiveness of RNNCon-Test. Compared to the current state-of-the-art study RNN-Test, RNNCon can cover a deeper decision logic of RNNs. RNNCon-Test is not only effective in identifying defects in Deep Learning (DL) systems but also in improving the performance of the model if the adversarial inputs generated by RNNCon-Test are filtered and added to the training set to retrain the model. In the case where the accuracy of the model is already high, RNNCon-Test is still able to improve the accuracy of the model by up to 0.45%. Full article

Terahertz massive MIMO systems can be used in the local area network (LAN) scene of maritime communication and has great application prospects. To solve the problems of excessive beam training overhead in beam tracking and beam splitting in beam aggregation, a broadband hybrid precoding (HP) is proposed. First, an additional delayer is introduced between each phase shifter and the corresponding antenna in the classical sub-connected HP structure. Then, by precisely designing the time delay of the delayer and the phase shift of the phase shifter, broadband beams with flexible and controllable coverage can be generated. Finally, the simulation results verify that the proposed HP can achieve fast-tracking and high-energy-efficient communication for multiple mobile users. Full article

Background: Vaccination hesitancy and skepticism among parents hinders progress in achieving full vaccination coverage. Swedish measles, mumps and rubella (MMR) vaccine coverage is high however some areas with low vaccination coverage risk outbreaks. This study aimed to explore factors influencing the decision of Somali parents living in the Rinkeby and Tensta districts of Stockholm, Sweden, on whether or not to vaccinate their children with the measles, mumps and rubella (MMR) vaccine. Method: Participants were 13 mothers of at least one child aged 18 months to 5 years, who were recruited using snowball sampling. In-depth interviews were conducted in Somali and Swedish languages and the data generated was analysed using qualitative content analysis. Both written and verbal informed consent were obtained from participants. Results: Seven of the mothers had not vaccinated their youngest child at the time of the study and decided to postpone the vaccination until their child became older (delayers). The other six mothers had vaccinated their child for MMR at the appointed time (timely vaccinators). The analysis of the data revealed two main themes: (1) barriers to vaccinate on time, included issues surrounding fear of the child not speaking and unpleasant encounters with nurses and (2) facilitating factors to vaccinate on time, included heeding vaccinating parents’ advice, trust in nurses and trust in God. The mothers who had vaccinated their children had a positive impact in influencing other mothers to also vaccinate. Conclusions: Fear, based on the perceived risk that vaccination will lead to autism, among Somali mothers in Tensta and Rinkeby is evident and influenced by the opinions of friends and relatives. Child Healthcare Center nurses are important in the decision-making process regarding acceptance of MMR vaccination. There is a need to address mothers’ concerns regarding vaccine safety while improving the approach of nurses as they address these concerns. Full article