Metal halide perovskite materials have been widely developed for next-generation light-emitting diodes (LEDs) because of their outstanding optoelectronic characteristics. However, it remains impediments to fabricate l...
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With the ongoing advancements in science and technology and the increasing research focus on cancer-related issues, there has been a proliferation of omics-related resources for in-depth analysis and exploration. This...
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Recently, the use of an unbounded external archive in the design of evolutionary multi-objective optimization (EMO) algorithms has received increasing attention. An important component in the use of an unbounded exter...
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Renewable energy generation sources (RESs) are gaining increased popularity due to global efforts to reduce carbon emissions and mitigate effects of climate change. Planning and managing increasing levels of RESs, spe...
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High-sensitivity room-temperature multi-dimensional infrared(IR)detection is crucial for military and civilian ***,the gapless electronic structures and unique optoelectrical properties have made the two-dimensional(2...
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High-sensitivity room-temperature multi-dimensional infrared(IR)detection is crucial for military and civilian ***,the gapless electronic structures and unique optoelectrical properties have made the two-dimensional(2D)topological semimetals promising candidates for the realization of multifunctional optoelectronic ***,we demonstrated the in-situ construction of high-performance 1T’-MoTe_(2)/Ge Schottky junction device by inserting an ultrathin AlOx passivation *** good detection performance with an ultra-broadband detection wavelength range of up to 10.6 micron,an ultrafast response time of~160 ns,and a large specific detectivity of over 109 Jones in mid-infrared(MIR)range surpasses that of most 2D materials-based IR sensors,approaching the performance of commercial IR *** on-chip integrated device arrays with 64 functional detectors feature high-resolution imaging capability at room *** these outstanding detection features have enabled the demonstration of position-sensitive detection *** demonstrates an exceptional position sensitivity of 14.9 mV/mm,an outstanding nonlinearity of 6.44%,and commendable trajectory tracking and optoelectronic demodulation *** study not only offers a promising route towards room-temperature MIR optoelectronic applications,but also demonstrates a great potential for application in optical sensing systems.
Recently, several real-world multi-objective optimization problem suites have been proposed to facilitate the evaluation of the performance of evolutionary multi-objective optimization (EMO) algorithms. In spite of th...
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We propose dynamic modulations of a photonic molecule to achieve topological properties of light. We investigate the Hall transport in synthetic dimensions and the system modulation strategy to demonstrate the pumping...
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Automated wildlife reidentification has attracted increasing attention in recent years as it provides a non-invasive tool to identify and to track individual wild animals over time. In this paper, the first steps are ...
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Automated wildlife reidentification has attracted increasing attention in recent years as it provides a non-invasive tool to identify and to track individual wild animals over time. In this paper, the first steps are taken towards the automatic photo-identification of the Ladoga ringed seals (Pusa hispida ladogensis). A method is proposed that takes a sequence of images, each containing multiple individuals as the input, and produces cropped images of seals grouped based on one certain individual per group. The method starts by detecting each seal from the images and proceeds to matching the individual seals between the images. It is shown that high grouping accuracy can be obtained with a general-purpose image retrieval method on an image sequence taken from the same location within a relatively short period of time. Each resulting group contains multiple images of one individual with slightly different variations, for example, in pose and illumination. Utilizing these images simultaneously provides more information for the individual re-identification compared to the traditional approach, i.e., which utilizes just one image at a time. It is further demonstrated that a convolutional neural network based method can be used to extract the unique pelage patterns of the seals despite the low contrast. Finally, a method is proposed and experiments with the novel Ladoga ringed seals data are carried out to provide a proof-of-concept for the individual re-identification.
We observed first asymmetric Hong-Ou-Mandel (HOM) revival interferences in a singly-filtered biphoton frequency comb. We measure up to 10 time-bins, and the witnessed central HOM dip has an accidental-subtracted visib...
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Convolutional Neural Networks (CNN) are widely employed in the contemporary artificial intelligence systems. However these models have millions of connections between the layers, that are both memory prohibitive and c...
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Convolutional Neural Networks (CNN) are widely employed in the contemporary artificial intelligence systems. However these models have millions of connections between the layers, that are both memory prohibitive and computationally expensive. Employing these models on an embedded mobile application is resource limited with high power consumption and significant bandwidth requirement to access the data from the off-chip DRAM. Reducing the data movement between the on-chip and off-chip DRAM is the main criteria to achieve high throughput and overall better energy efficiency. Our proposed multi-bit accelerator achieves these goals by employing the truncation of the partial sum (Psum) results of the preceding layer before feeding it into the next layer. We exhibit the architecture by inferencing 32-bits for the first convolution layers and sequentially truncate the bits on the MSB/LSB of integer and fractional part without any further training on the original network. At the last fully connected layer, the top-1 accuracy is maintained with the reduced bit width of 14 and top-5 accuracy upto 10-bit width. The computation engine consists of an systolic array of 1024 processing elements (PE). Large CNNs such as AlexNet, MobileNet, SqueezeNet and EfficientNet were used as benchmark CNN model and Virtex Ultrascale FPGA was used to test the architecture. The proposed truncation scheme has 49% power reduction and resource utilization was reduced by 73.25% for LUTs (Look-up tables), 68.76% for FFs (Flip-Flops), 74.60% for BRAMs (Block RAMs) and 79.425% for Digital Signal Processors (DSPs) when compared with the 32 bits architecture. The design achieves a performance of 223.69 GOPS on a Virtex Ultrascale FPGA, the design has a overall gain of 3.63 × throughput when compared to other prior FPGA accelerators. In addition, the overall power consumption is 4.5 × lower when compared to other prior architectures. The ASIC version of the accelerator was designed in 22nm FDSOI CMOS proc
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