We present a study of byte pair encoding (BPE) based language modeling for open vocabulary Latin language OCR. On a large-scale handwritten English OCR task, we demonstrate that a simple BPE-based n-gram language model (LM) can deal with out-of-vocabulary word problem effectively and achieve better accuracy-footprint tradeoff than a state-of-the-art hybrid word/subword n-gram LM interpolated by a standard hybrid LM, a word-based LM, and a subword-based LM. On another large-scale printed OCR task for six Latin languages, namely English, Spanish, French, German, Italian, and Portuguese, we discover that a unified OCR system with a single character-based optical model and a single BPE-based n-gram LM shared by six languages performs better than language-dependent OCR systems. BPE-based LM offers a good product solution for both monolingual and multilingual open-vocabulary Latin language OCR.

Smart contracts (SCs) run on the distributed ledger technology (DLT) platform and can implement agreements between participants without a trusted third party. This paper uses the DLT and SC techniques to build distributed applications composed of existing services. In practice, there are many functionally-equivalent services on the Internet. To beat their competitors, the service providers usually offer flexible QoS and use dynamic pricing strategies. Moreover, the service providers can change at runtime, e.g., they may encounter problems so that their QoS drops suddenly. This makes achieving the optimization goal at runtime (e.g., the maximization of the utility) more difficult. To address this problem, first, this paper proposes an SC-based negotiation framework. The SCs can ensure that the transactions are automatically and reliably performed as agreed upon between the service requesters and providers. The DLTs can provide the reliable data of the requests and responses of the service requesters and providers to the SCs. In addition, the SCs can identify the troubled service providers, and find other service providers to replace them at runtime. Second, this paper proposes a Bayesian Nash equilibrium (BNE) of the service providers. In the BNE, the cost-efficient service providers offer the high QoS the service requester asks for and report their costs truthfully. This BNE enables the selection of the cost-efficient service providers and the achievement of the (near) maximization of the service requesters' utility. This paper implements the proposed negotiation framework on a DLT platform called Hyperledger Fabric. The experiment results demonstrate that the proposed approach outperforms the existing approaches and can adapt to the changes of the service providers.