Intelligent Property Research Articles

중국 게임 <원신>의 트랜스-내셔널 스토리월드 구축

In the era of the 4th industrial revolution, it is undeniable that the cultural and economic impact of the game industry, which is the forefront industry of the IP (Intelligent Property) value chain, is becoming increasingly important. Amid this trend, identifying recent trends in the game industry and major game contents in other countries and analyzing their success factors are essential tasks for cultural content industry and its researchers. Meanwhile, China, not only as a content consumer but also as a content producer, is increasing its influence in all directions through the expansion of IT infrastructure in line with its rapid economic growth. In this context, this article targets China's open-world CCG RPG game Genshin Impact. The game emerges as an important analysis target in several contexts, including its popularity established in the global game market and its special position as a ‘Chinese game’. In terms of content creation, operation, and marketing, this article aims to analyze Genshin Impact’s Trans-nationality strategy beyond ‘Chinese characteristics’ or ‘Chinese characteristics’. Secondly, this article focus on the ‘Character Moe’ code that functions as a key mechanism of the storyworld construction and a business model of this game. Through this, this article intends to examine the reason of Genshin Impact’s global success and popularity as a trans-national storyworld.

Block-chain based federated learning for knowledge capital

With the rapid development of deep learning and structures of neural networks, parameter settings of trained neural networks become new products from knowledge. Since supervised learning is used in 85% of machine learning to train the neural networks, well-labeled training data becomes new knowledge capital. In order to stimulate the knowledge sharing and protect the Intelligent Property (IP) right and privacy of knowledge capital at the same time, we need a framework to conduct training of neural networks with certain encrypted data and exchange training results with certain rewards. Federated learning provides a framework to train the networks without disclose the privacy and a block-chain based transaction system can organize a group of participants under certain consensus and reward mechanism. Their combination is an effective solution to manage knowledge capital, called knowledge capital bank in this paper. This paper defines the economic meaning of knowledge capital and all behaviors of related participants. Then we propose a block-chain based federated learning algorithm for secured knowledge sharing with IP and privacy protection. Finally, a complete design for a use case of this algorithm called Knowledge capital bank is demonstrated.

A real-time inverse quantised transform for multi-standard with dynamic resolution support

ABSTRACTIn this paper, a real-time configurable intelligent property (IP) core is presented for image/video decoding process in compatibility with the standard MPEG-4 Visual and the standard H.264/AVC. The inverse quantised discrete cosine and integer transform can be used to perform inverse quantised discrete cosine transform and inverse quantised inverse integer transforms which only required shift and add operations. Meanwhile, COordinate Rotation DIgital Computer iterations and compensation steps are adjustable in order to compensate for the video compression quality regarding various data throughput. The implementations are embedded in publicly available software XVID Codes 1.2.2 for the standard MPEG-4 Visual and the H.264/AVC reference software JM 16.1, where the experimental results show that the balance between the computational complexity and video compression quality is retained. At the end, FPGA synthesised results show that the proposed IP core can bring advantages to low hardware costs and also provide real-time performance for Full HD and 4K–2K video decoding.

Manufacturing Aspect of the IBCA Structure for Active Knowledge Content Representation in Product Model

Integration of all engineering activities for lifecycle of very complex multidisciplinary products in product lifecycle management (PLM) system has lead to very complex product models in leading industries. Product model was initially defined in the ISO 10303 standard by the International Organization for Standardization (ISO). In recent advanced PLM modeling, complexity of product is handled by knowledge driven self adaptive generic model while multidisciplinary conceptual modeling applies higher abstraction methods from systems engineering (SE). Company and personal experience and expertise based active knowledge is included in product model and accumulated as intelligent property (IP) of company. Higher abstraction levels have been included by using of requirement, functional, logical, and physical (RFLP) structure of product model. In the context of physical (P) level product information, product realization (PR) model structure is defined. PR includes model information for manufacturing processes, systems, and resources.The above scenario motivated research at the Laboratory of Intelligent Engineering Systems (LIES) in high level abstraction and request driven generation of RFLP and product realization (PR) structure elements in product model. This paper introduces new research results in the initiative, behavior, context and action (IBCA) structure. Two purposes of IBCA structure are to organize active IP in product model and driving generation of RFLP and PR structure elements using always actual IP. Next issue in this paper is analysis of possibility for connection PR model entities to active knowledge driven RFLP structure element definitions. In order to achieve industrially applicable solution, research results in IBCA structure can be implemented in any host industrial PLM system where RFLP and PR structures are available within a contextual product model system. IBCA structure is required to utilize special problem solving capabilities of soft computing methods.