Contract production and transaction are very common and important since it can greatly reduce future uncertainty and is well-organized by buyers, sellers, and trusted third parties (TTPs). However, current commodity trading systems (such as spot, futures, and forward contract) are still traditional centralized structures, which means that there may always be concerned about the single point of failure and data corruption. Besides, even though there already exists fragmentary decentralized applications (DApps) for the marketplace, order management, resale, delivery, financing, and insurance, they are not integrated for operating contract production and transaction comprehensively. In this work, a blockchain-enabled integrated marketing platform (BeIMP) is proposed for contract production and transactions. BeIMP is a consortium blockchain (CsBc) framework that enables better safety, efficiency, and interoperability among stakeholders. BeIMP can directly match producers and consumers and reduce the problem of intermediaries' improper market operation. BeIMP has a three-tier risk diversification mechanism. First, both parties can know the quantity and price according to the contract specification (CSpec) in advance to avoid future uncertainty. Second, the buyers can resell the established order if they need, thereby diversifying the risk. Third, the concept of insurance is introduced to reduce force majeure and other systemic risks. BeIMP can also help producers get the loan from the financial institution (FI) if they need fund for production. We implement and demonstrate the prototype in contract farming (CF) first and discuss its generalizability to other scenarios. Experiment results show that the smart contract (SC) function is stable enough and the proof of authority (PoA) has the advantage in throughput and can give users a better experience.

We have developed a local search algorithm to enhance the computational efficiency of digital image correlation (DIC). This work examined the biaxial strain and Poisson's ratio of a deformed ASTM B557M specimen using a modified model of DIC. We have also developed a model to enable the precise cropping of large images in order to reduce the numerical cost associated with pattern searches within an image stack. The proposed DIC system produces time-displacement curves based on pattern tracking as well as time-strain curves through numerical differentiation. In the region of elastic deformation, the system provides results consistent with those obtained using strain gauges and material testing systems (MTSs). Local deformation at the microscopic scale is captured using a newly developed DIC program, which outputs raw data corresponding to the vertical and horizontal directions. The proposed DIC system yields clear images with 4K resolution (4096 × 2160 pixels) and high spatial resolution of 1.9 µm based on a program that uses a numerical gradient to locate peaks in correlated results. Specimen preparation is simple, requiring only the application of speckle on the surfaces of featureless objects. The experimental setup requires only one laptop computer and one or more digital cameras from many manufacturers. The proposed DIC program can be embedded within a variety of MTSs, providing precision measurements for a wide variety of applications.