New applications such as CAD, AI, and hypermedia require direct representation and flexible use of complex objects, behavioral knowledge, and multimedia data. To this end, we have devised a knowledge base management system called Jasmine. An object-oriented approach in a programming language also seems promising for use in Jasmine. Jasmine extends the current object-oriented approach and provides the following features. Our object model is based on functional data models and well-established set theory. Attributes or functions composing objects can represent both structural and behavioral knowledge. The object model can represent incomplete and generic knowledge. The model can support the basic storage and operations of multimedia data. The facets of attributes can flexibly represent constraints and triggers. The object manipulation language can support associative access of objects. The structural and behavioral knowledge can be uniformly treated to allow the user to specify complex object operations in a compact manner. The user-defined and system-defined attributes can be uniformly specified to ease user customization of the language. The classes and instances can be uniformly accessed. Incomplete knowledge can be flexibly accessed. The system has a layered architecture. Objects are stored in nested relations provided by extensive DBMS as a sublayer. User query of objects is compiled into relational operations such as select and join, which can be efficiently processed using hashing. The behavioral knowledge is compiled into predicate and manipulation function interfaces that can directly access tuples in a buffer.— Authors' Abstract

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The total number of solar power-producing facilities whose Feed-in Tariff (FIT) Program-based ten-year contracts will expire by 2023 is expected to reach approximately 1.65 million in Japan. If the facilities that produce or consume renewable energy would increase to reach a large number, e.g., two million, blockchain would not be capable of processing all the transactions. In this work, we propose a blockchainbased electricity-tracking platform for renewable energy, called 'ZGridBC,' which consists of mutually cooperative two novel decentralized schemes to solve scalability, storage cost, and privacy issues at the same time. One is the electricity production resource management, which is an efficient data management scheme that manages electricity production resources (EPRs) on the blockchain by using UTXO tokens extended to two-dimension (period and electricity amount) to prevent double-spending. The other is the electricity-tracking proof, which is a massive data aggregation scheme that significantly reduces the amount of data managed on the blockchain by using zero-knowledge proof (ZKP). Thereafter, we illustrate the architecture of ZGridBC, consider its scalability, security, and privacy, and illustrate the implementation of ZGridBC. Finally, we evaluate the scalability of ZGridBC, which handles two million electricity facilities with far less cost per environmental value compared with the price of the environmental value proposed by METI (= 0.3 yen/kWh).