Machine fault diagnosis with small sample based on variational information constrained generative adversarial network

In actual engineering scenarios, limited fault data leads to insufficient model training and over-fitting, which negatively affects the diagnostic performance of intelligent diagnostic models. To solve the problem, this paper proposes a variational information constrained generative adversarial network (VICGAN) for effective machine fault diagnosis. Firstly, by incorporating the encoder into the discriminator to map the deep features, an improved generative adversarial network with stronger data synthesis capability is established. Secondly, to promote the stable training of the model and guarantee better convergence, a variational information constraint technique is utilized, which constrains the input signals and deep features of the discriminator using the information bottleneck method. In addition, a representation matching module is added to impose restrictions on the generator, avoiding the mode collapse problem and boosting the sample diversity. Two rolling bearing datasets are utilized to verify the effectiveness and stability of the presented network, which demonstrates that the presented network has an admirable ability in processing fault diagnosis with few samples, and performs better than state-of-the-art approaches.     

Electrodeposition of the manganese-doped nickel-phosphorus catalyst with enhanced hydrogen evolution reaction activity and durability

Hydrogen technology is widely considered a novel clean energy source, and electrolysis is an effective method for hydrogen evolution. Therefore, efficient hydrogen evolution reaction (HER) catalysts are urgently needed to replace precious metal catalysts and meet ecological and environmental protection standards. Herein, Ni–Mn–P electrocatalysts are synthesized using facile electrodeposition technology. The influence of the Mn addition on the catalytic behavior is studied by the comprehensive analysis of catalytic performance and morphology of the catalysts. Among them, the Ni–Mn–P0.01 catalyst exhibits small coral-like structures, greatly improving the adsorption and desorption of hydrogen ions and reducing the overpotential hydrogen evolution. Consequently, overpotential at 10 mA cm^?2 electric current density is 113 mV, and the value of the Tafel slope achieves 74 mV/dec. Furthermore, the Ni–Mn–P catalyst shows long-time (20 h) stability at current densities of 10 and 60 mA/cm². The results confirm that the synergistic effect of Ni, Mn, and P accelerates the electrochemical reaction. Meanwhile, the addition of manganese element can change the micromorphology of the catalyst, thereby exposing more active sites to participate in the reaction, enhancing water ionization, improving the catalytic performance. This study opens a new way toward improving the activity of the catalyst by adjusting Mn concentration during the electrodeposition process.     

YOLSO: You Only Look Small Object

Small object detection is challenging and far from satisfactory. Most general object detectors suffer from two critical issues with small objects: (1) Feature extractor based on classification network cannot express the characteristics of small objects reasonably due to insufficient appearance information of targets and a large amount of background interference around them. (2) The detector requires a much higher location accuracy for small objects than for general objects. This paper proposes an effective and efficient small object detector YOLSO to address the above problems. For feature representation, we analyze the drawbacks in previous backbones and present a Half-Space Shortcut(HSSC) module to build a background-aware backbone. Furthermore, a coarse-to-fine Feature Pyramid Enhancement(FPE) module is introduced for layer-wise aggregation at a granular level to enhance the semantic discriminability. For loss function, we propose an exponential L1 loss to promote the convergence of regression, and a focal IOU loss to focus on prime samples with high classification confidence and high IOU. Both of them significantly improves the location accuracy of small objects. The proposed YOLSO sets state-of-the-art results on two typical small object datasets, MOCOD and VeDAI, at a speed of over 200 FPS. In the meantime, it also outperforms the baseline YOLOv3 by a wide margin on the common COCO dataset.     

Optimal data-based binning for histograms and histogram-based probability density models

Histograms are convenient non-parametric density estimators, which continue to be used ubiquitously. Summary quantities estimated from histogram-based probability density models depend on the choice of the number of bins. We introduce a straightforward data-based method of determining the optimal number of bins in a uniform bin-width histogram. By assigning a multinomial likelihood and a non-informative prior, we derive the posterior probability for the number of bins in a piecewise-constant density model given the data. In addition, we estimate the mean and standard deviations of the resulting bin heights, examine the effects of small sample sizes and digitized data, and demonstrate the application to multi-dimensional histograms.     

Estonian urbanism 1935–1955: the Soviet-era implementation of pre-war ambitions

Estonian 1940s–1950s town planning practices show that Stalinist principles were in line with those of Estonian architects during the 1930s pre-war, independence period. However, between 1944 and 1955, within the context of the Soviet regime’s occupation, urban planning was faced with rigid ideological constraints. After the Second World War, Estonian architects were forced to abandon projects in historical city centres, which focused on maintaining local natural conditions and cultural heritage, as well as using local materials. Some existing town centres, such as in Tallinn, Narva, and Pärnu, were reconstructed after suffering damage in the war, as well as for ideological reasons. Yet, during this time period, most efforts were directed towards building new industrial towns in East Estonia that exemplified a Stalinist utopia; this also presented the Soviet regime with an opportunity to exploit local mineral resources.     

Compiler compatible 5.66 Mb/mm2 8T 1R1W register file in 14 nm FinFET technology

1-read/1-write (1R1W) register file (RF) is a popular memory configuration in modern feature rich SoCs requiring significant amount of embedded memory. A memory compiler is constructed using the 8T RF bitcell spanning a range of instances from 32 b to 72 Kb. An 8T low-leakage bitcell of 0.106 μm² is used in a 14 nm FinFET technology with a 70 nm contacted gate pitch for high-density (HD) two-port (TP) RF memory compiler which achieves 5.66 Mb/mm² array density for a 72 Kb array which is the highest reported density in 14 nm FinFET technology. The density improvement is achieved by using techniques such as leaf-cell optimization (eliminating transistors), better architectural planning, top level connectivity through leaf-cell abutment and minimizing the number of unique leaf-cells. These techniques are fully compatible with memory compiler usage over the required span. Leakage power is minimized by using power-switches without degrading the density mentioned above. Self-induced supply voltage collapse technique is applied for write and a four stack static keeper is used for read Vmin improvement. Fabricated test chips using 14 nm process have demonstrated 2.33 GHz performance at 1.1 V/25 °C operation. Overall V_min of 550 mV is achieved with this design at 25 °C. The inbuilt power-switch improves leakage power by 12x in simulation. Approximately 8% die area of a leading 14 nm SoC in commercialization is occupied by these compiled RF instances.     

冷链仓储创新装备在河南鲁山精准扶贫中的应用分析

文章对鲁山县董周乡酥梨冷箱仓储扶贫试点应用项目的实施情况开展了专题调研,现将多功能模块化组合冷箱配套农产品市场经营策略精准促进鲁山县董周乡农村产业扶贫的实施情况做系统阐述。     

Alternatives for improving energy security in Cape Verde

The lack of consensus on the meaning of energy security and how it should be measured hinders the evaluation of alternatives for improving the Cape Verdean energy sector. The objective of the paper is to develop an energy security index adjusted to the country's context. The methods used are the multi-criteria analysis and the Delphi survey. Different alternatives to improve energy security are assessed: electrically interconnect Cape Verde's islands, increase the share of renewable energy, and a combination of the previous alternatives. The results of our analysis indicate that increasing renewable energy is the optimal alternative for Cape Verde.     

In-situ modification of PEDOT:PSS work function using alkyl alcohols as secondary processing solvents and their impact on merocyanine based bulk heterojunction solar cells

The influence of a series of alkyl alcohols on the work function of PEDOT:PSS thin films is systematically investigated by Kelvin probe measurements. We show that the PEDOT:PSS work function can be increased stepwise from 5.2 eV for pristine PEDOT:PSS to 5.61 eV using either alcohols with different alkyl chain length or varying the amount of alcohol in mixtures with chlorobenzene. Moreover, we demonstrate the effect of work function modification on merocyanine based bulk heterojunction solar cells, resulting in improved values for the open-circuit voltage comparable to those obtained with high work function MoO₃. Thus, the processing method presented herein can potentially serve as a simple, alternative route to adjustable and high work function electrodes while maintaining processability from solution.