Academic literature on the topic 'Lightermen'

When Anthonis Van den Wyngaerde executed his sweeping panorama of London in 1543, he drew some two dozen ships in the Thames, but only four of them downstream from St. Katherine's Dock. A century later, however, Wenceslaus Hollar carefully represented well over a hundred seagoing vessels in a ribbon of masts winding down river as far as the eye could see. By the 1650s a mariner noted the difficulty of navigating the Thames at low tide, especially during “mackerel time,” and Admiralty Judges at Doctors' Commons near St. Paul's were hearing complaints that congestion in the river was endangering London's environment. Petitioners alleged in 1658 that Jenkin Ellis, a shoemaker and wharf owner, had so exploited his foothold of just ten yards along the north shore of the river, by selling permission to anchor ships eight-and ten-abreast, that the entire bank from St. Katherine's Stairs to the Dock was ruined. It had once been, said witnesses, a “fair sandy ground” where “people might pass on foot,” where watermen could “wax and tallow their boats.” But after Ellis had arrived in 1640, the bank slowly turned to “mud…ooze and dirt,” and “the current of the Thames near shore” where the ships lay was now so “hindered…that if not timely prevented,” the river would be “choked up.” Fires carelessly tended aboard the ships when they were grounded at low tide threatened houses in the entire precinct. When riding at anchor near the shoemaker's wharf, the vessels forced lightermen to row in midriver “against the strength and current of the tide.”The rising number of ships in English waterways had apparently reduced everyone's margin for error in the seventeenth century. For collisions in the Thames and elsewhere were providing the civil lawyers of London's Admiralty Court with a stream of cases. Ironically, this litigation, it is argued here, reveals both the resourcefulness of England's maritime judges and the major cause of a decline in their authority during the late Stuart decades.

In unmanned aerial vehicle based urban observation and monitoring, the performance of computer vision algorithms is inevitably limited by the low illumination and light pollution caused degradation, therefore, the application image enhancement is a considerable prerequisite for the performance of subsequent image processing algorithms. Therefore, we proposed a deep learning and generative adversarial network based model for UAV low illumination image enhancement, named LighterGAN. The design of LighterGAN refers to the CycleGAN model with two improvements—attention mechanism and semantic consistency loss—having been proposed to the original structure. Additionally, an unpaired dataset that was captured by urban UAV aerial photography has been used to train this unsupervised learning model. Furthermore, in order to explore the advantages of the improvements, both the performance in the illumination enhancement task and the generalization ability improvement of LighterGAN were proven in the comparative experiments combining subjective and objective evaluations. In the experiments with five cutting edge image enhancement algorithms, in the test set, LighterGAN achieved the best results in both visual perception and PIQE (perception based image quality evaluator, a MATLAB build-in function, the lower the score, the higher the image quality) score of enhanced images, scores were 4.91 and 11.75 respectively, better than EnlightenGAN the state-of-the-art. In the enhancement of low illumination sub-dataset Y (containing 2000 images), LighterGAN also achieved the lowest PIQE score of 12.37, 2.85 points lower than second place. Moreover, compared with the CycleGAN, the improvement of generalization ability was also demonstrated. In the test set generated images, LighterGAN was 6.66 percent higher than CycleGAN in subjective authenticity assessment and 3.84 lower in PIQE score, meanwhile, in the whole dataset generated images, the PIQE score of LighterGAN is 11.67, 4.86 lower than CycleGAN.

Concrete is a composite building material that functions very widely in the field of construction. This object is quite environmentally friendly in its application, because its existence can reduce the use of wood in the world of construction construction. But the size of the excess weight that is owned by the concrete structure when compared with wood is still less efficient, especially in the application for building construction with a building height of more than one floor. lighter.On this occasion we tried to use a number of aggregate combinations to design a lightweight concrete formula mix design to match the specified spec. The composition and aggregates that we use are type I portland cement, Master Ease 5010 additive, Hydroton, Batu Gombong as coarse aggregates and sand which are used as fine aggregates. Hydrotonini has hard and light characteristics. Shaped like spheres - small spheres measuring 1 - 2.5cm, usually used as alternative planting media in general. With such characteristics Hydroton is considered able to be used as a coarse aggregate substitute in the manufacture of lightweight concrete job mixes