A novel region-based multimodal image fusion technique using improved dictionary learning

Recently, the sparse representation (SR) based algorithms have gained much attention from the researchers in the area of image fusion (IF). The building of a compact discriminative dictionary plays a vital role in the sparse-based IF techniques. In this context, an efficient multimodal IF method based on improved dictionary learning is investigated. The key contributions of this paper are: (a) An improved KSVD algorithm is suggested for the dictionary learning process, (b) to reduce the computational time, only the informative patches are selected using energy feature, and (c) a novel region-based fusion scheme is suggested for the first time for the problem on hand. The suggested technique is tested with a number of multimodal images from Harvard Medical School brain database. The results are compared with state-of-the-art multiscale transform-based methods and modified SR-based methods. Unlike earlier methods, our proposed technique generates an adaptive dictionary through selection of informative patches only. This results in a compact dictionary with improved computational efficiency. The experimental results reveal that our approach outperforms other methods. The potential application of the suggested method could be in pathological images for follow-up study and better treatment planning.     

Black hole entropy,the black hole information paradox,and time travel paradoxes from a new perspective

ABSTRACT

Relatively simple but apparently novel ways are proposed for viewing three related subjects: black hole entropy, the black hole information paradox, and time travel paradoxes. (1) Gibbons and Hawking have completely explained the origin of the entropy of all black holes, including physical black holes – nonextremal and in 3-dimensional space – if one can identify their Euclidean path integral with a true thermodynamic partition function (ultimately based on microstates). An example is provided of a theory containing this feature. (2) There is unitary quantum evolution with no loss of information if the detection of Hawking radiation is regarded as a measurement process within the Everett interpretation of quantum mechanics. (3) The paradoxes of time travel evaporate when exposed to the light of quantum physics (again within the Everett interpretation), with quantum fields properly described by a path integral over a topologically nontrivial but smooth manifold.     

Temporal information based GoP adaptation for linear video delivery schemes

An original wireless video transmission scheme called SoftCast has been recently proposed to deal with the issues encountered in conventional wireless video broadcasting systems (e.g. cliff effect). In this paper, we evaluate and optimize the performance of the SoftCast scheme according to the transmitted video content. Precisely, an adaptive coding mechanism based on GoP-size adaptation, which takes into account the temporal information fluctuations of the video, is proposed. This extension denoted Adaptive GoP-size mechanism based on Content and Cut detection for SoftCast (AGCC-SoftCast) significantly improves the performance of the SoftCast scheme. It consists in modifying the GoP-size according to the shot changes and the spatio-temporal characteristics of the transmitted video. When hardware capacities, such as buffer or processor performance are limited, an alternative method based only on the shot changes detection (AGCut-SoftCast) is also proposed. Improvements up to 16 dB for the PSNR and up to 0.55 for the SSIM are observed with the proposed solutions at the cut boundaries. In addition, temporal visual quality fluctuations are reduced under 1dB in average, showing the effectiveness of the proposed methods.     

基于GFU和分层LSTM的组群行为识别研究方法

提出一种以"关键人物"为核心，使用门控融合单元（GFU，Gated Fusion Unit）进行特征融合的组群行为识别框架，旨在解决两个问题：①组群行为信息冗余，重点关注关键人物行为特征，忽略无关人员对组群行为的影响；②组群内部交互行为复杂，使用GFU有效融合以关键人物为核心的交互特征，再通过LSTM时序建模成为表征能力更强的组群特征.最终，通过softmax分类器进行组群行为类别分类.该算法在排球数据集上取得了86.7%的平均识别率.     

自适应融合层级特征的混合退化图像复原算法

多种退化类型混合的图像比单一类型的退化图像降质更严重,很难建立精确模型对其复原,研究端到端的神经网络算法是复原的关键.现有的基于操作选择注意力网络的算法(operation-wiseattentionnetwork,OWAN)虽然有一定的性能提升,但是其网络过于复杂,运行较慢,复原图像缺乏高频细节,整体效果也有提升的空间.针对这些问题,提出一种基于层级特征融合的自适应复原算法.该算法直接融合不同感受野分支的特征,增强复原图像的结构;用注意力机制对不同层级的特征进行动态融合,增加模型的自适应性,降低了模型冗余;另外,结合L1损失和感知损失,增强了复原图像的视觉感知效果.在DIV2K,BSD500等数据集上的实验结果表明,该算法无论是在峰值信噪比和结构相似性上的定量分析,还是在主观视觉质量方面,均优于OWAN算法,充分证明了该算法的有效性.     

Process parameter dependencies of continuous and pulsed laser modes on surface polishing of additive manufactured aluminium AlSi10Mg parts

Laser powder bed fusion is a well-established 3D printing technique for metal alloys, but exhibits a poor surface quality. Laser polishing provides the possibility of a fast contact-free and fully-automatable surface treatment. This paper deals with the experimental investigation of laser polishing of laser powder bed fusion parts made of aluminium AlSi10Mg. Laser polishing is done with a 4 kW solid state disc laser in combination with a multi-axis system and a one dimensional scanner optic. The laser is operated at continuous and pulsed operation mode. The parameter study reveals a high dependency of the achievable roughness on the laser beam intensity, the track and pulse overlap, the energy density and the number of polishing passes and polishing directions. Pulsed laser polishing mode with up to four passes from different directions revealed the lowest surface roughness of 0.14 μm Ra. With respect to the initial average surface roughness of Ra = 8.03 μm a reduction of the surface roughness of greater than 98 % could be achieved. Polishing with continuous laser radiation at one polishing pass resulted in Ra = 0.23 μm at an area rate of 20 cm²/min. Laser polishing using four passes achieved a further improvement up to Ra = 0.14 μm.     

Additive manufacturing of bipolar plates for hydrogen production in proton exchange membrane water electrolysis cells

Water electrolysis is a process that can produce hydrogen in a clean way when renewable energy sources are used. This allows managing large renewable surpluses and transferring this energy to other sectors, such as industry or transport. Among the electrolytic technologies to produce hydrogen, proton exchange membrane (PEM) electrolysis is a promising alternative. One of the main components of PEM electrolysis cells are the bipolar plates, which are machined with a series of flow distribution channels, largely responsible for their performance and durability. In this work, AISI 316L stainless steel bipolar plates have been built by additive manufacturing (AM), using laser powder bed fusion (PBF-L) technology. These bipolar plates were subjected to ex-situ corrosion tests and assembled in an electrolysis cell to evaluate the polarization curve. Furthermore, the obtained results were compared with bipolar plates manufactured by conventional machining processes (MEC). The obtained experimental results are very similar for both manufacturing methods. This demonstrates the viability of the PBF-L technology to produce metal bipolar plates for PEM electrolyzers and opens the possibilities to design new and more complex flow distribution channels and to test these designs in initial phases before scaling them to larger surfaces.     

基于GIS的航电枢纽安全监测信息管理系统设计与应用

为解决航电枢纽安全监测海量数据统筹管理以及GIS技术结合应用程度低等问题,开发了基于GIS的航电枢纽安全监测信息管理系统。倾斜摄影技术的应用实现了高效建立工程三维数字模型,通过实景模型与工程监测的结合,为监测点可视化管理及成果可视化展示提供了条件。系统实现的技术路线,可为类似工程项目提供参考。     

基于温度冲击的冷冻靶氘氘冰层结晶生长行为研究

惯性约束聚变冷冻靶中氘氘（D₂）冰层的质量对聚变实验的成功与否起重要作用。目前文献报道的制备冷冻靶D₂冰层的方法并不具备好的可操作性，且技术、工艺不定型，制约了高质量冰层的形成。因此，本文采用将温度梯度、降温速率和温度冲击相结合的技术实现燃料冰层在靶丸内的均化。通过温度控制以及施加温度冲击可控地形成残留冰，并在残留冰的控制技术基础上，实现了高质量冰层的可控结晶生长。同时，研究了温度控制对靶丸内D₂冰层品质的影响和D₂冰层结晶生长的过程，并应用晶体生长动力学理论分析了D₂冰层结晶生长行为。从背光阴影图像中的D₂冰层亮环可知，D₂冰层均匀度为85.2%、厚度为40.35 μm、内表面粗糙度为2.15 μm。本方法拓宽了超低温下D₂冰籽晶控制、晶体生长技术，为DT冷冻靶中冰层均化打下了坚实基础，并形成了一定的技术储备。