According to the central symmetry and bright-dark alteration of the four peripheral regions at the X-corner, an automated X-corner detection algorithm (AXDA) is presented to camera calibration problem. By detecting the gray changes of the image, the algorithm can locate the position of X-corner accurately using the minimum correlation coefficient of the symmetry regions. Cross points of intersection are calculated using the detection points and the least square straight line fitting algorithm. The method can not only realize the sub-pixel X-corner extraction, but also resolve the low automation degree problem of the present detection algorithm under complex background. Experiment results show that the algorithm is an easily-realized, highly-automated and robust method for rotation transform and brightness transform of the X-corner image
With the continuous development of organic semiconductor materials and on‐going improvement of device technology, the power conversion efficiencies (PCEs) of organic solar cells (OSCs) have surpassed the threshold of 19%. Now, the low production cost of organic photovoltaic materials and devices have become an imperative demand for its practical application and future commercialization. Herein, the feasibility of simplified synthesis for cost‐effective small‐molecule acceptors via end‐cap isomeric engineering is demonstrated, and two constitutional isomers, BTP‐m‐4Cl and BTP‐o‐4Cl, are synthesized and compared in parallel. These two non‐fullerene acceptors (NFAs) have very similar optoelectronic properties but nonuniform morphological and crystallographic characteristics. Consequently, the OSCs composed of PM6:BTP‐m‐4Cl realize PCE of 17.2%, higher than that of the OSCs with PM6:BTP‐o‐4Cl (≈16%). When ternary OSCs are fabricated with PM6:BTP‐m‐4Cl:BTP‐o‐4Cl, the averaged PCE value reaches 17.95%, presenting outstanding photovoltaic performance. Most excitingly, the figure of merit (FOM) values of PM6:BTP‐m‐4Cl, PM6:BTP‐o‐4Cl, and PM6:BTP‐m‐4Cl:BTP‐o‐4Cl based devices are 0.190, 0.178, and 0.202 respectively. The FOM values of these systems are all among the top ones of the current high‐efficiency OSC systems, revealing high cost‐effectiveness of the two NFAs. This work provides a general but accessible strategy to minimize the efficiency‐cost gap and promises the economic prospects of OSCs.
<p class="Abstract" style="margin: 0cm 0cm 0pt; layout-grid-mode: char;"><span style="font-size: x-small;"><span style="font-family: Times New Roman;"><span style="mso-bidi-font-size: 9.0pt;">Manufacturing supply chain(SC) faces changing business environment and various customer demands. Pareto Ant Colony Optimisation (P-ACO) in order to obtain the non-dominated set of different SC designs was utilized as the guidance for designing manufacturing SC. P-ACO explores the solution space on the basis of applying the Ant Colony Optimisation algorithm and implementing more than one pheromone matrix, one for every objective. The SC</span><span style="mso-bidi-font-size: 9.0pt; mso-fareast-language: ZH-CN;"> design</span><span style="mso-bidi-font-size: 9.0pt;"> problem has been addressed by using Pareto Ant Colony Optimisation in which two objectives are minimised simultaneously. There were tested two ways in which the quantity of pheromones in the PM is incremented. In the SPM, the pheromone increment is a function of the two objectives, cost and time, while in MPM the pheromone matrix is divided into two pheromones, one for the cost and another one for the time. It could be concluded that the number of solutions do not depend on if the pheromone is split or is a function of the two variables because both method explore the same solution space. Although both methods explore the same solution space, the POS generated by every one is different. The POS that is generated when the pheromone matrix is split got solutions with lower time and cost than SMP because in the probabilistic decision rule a value of λ = 0.2 is used. It means that the ants preferred solution with a low cost instead of solutions with low time. The strategy of letting the best-so-far ant deposit pheromone over the PM accelerates the algorithm to get the optimal POS although the number of ants in the colony is small.</span></span></span></p><p class="Abstract" style="margin: 0cm 0cm 0pt; layout-grid-mode: char;"><span style="mso-bidi-font-size: 9.0pt;"><span style="font-size: x-small;"><span style="font-family: Times New Roman;">An experimental example is used to test the algorithm and show the benefits of utilising two pheromone matrices and multiple ant colonies in SC optimisation problem.</span></span></span></p>
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