This study analyzed patent trends for technologies that convert horticultural crop residues into mushroom substrates and developed mycelium-based utilization technologies. Environmental pollution caused by disposable plastics and Styrofoam has increased. Therefore, the demand for innovative and eco-friendly solutions has substantially increased. Agricultural residues such as fruit pruning residues and citrus waste provide economically and environmentally viable alternatives to imported raw materials because of their rich cellulose and lignin contents. Recent studies have shown that substrates containing these residues can produce mushrooms of equivalent quality as conventional sawdust-based media, thereby reducing production costs and improving resource independence. In addition, mushroom mycelia have been developed as sustainable materials for non-animal leather, packaging, building, and insulation. A patent analysis of ECOVATIVE confirmed important innovations in processing, material mixing, and product applications. The results provide the foundation for building an integrated system for utilizing horticultural residue resources with mycelium-based materials, as well as offers strategic insights and future directions for the research and development of sustainable industrial materials. The results also demonstrate the potential of agricultural byproducts to reduce dependence on imported substrates, lower cultivation costs, and mitigate environmental impacts, ultimately contributing to a circular economy for the development of sustainable materials.

본 연구의 목적은 국내 전력산업의 새로운 성장동력인 HVDC를 기술적 관점의 연구가 아닌 특허 기반의 서지계량학적 분석을 통해 기술의 발전 흐름과 핵심 기술군을 파악 하고자 하였다. HVDC 관련 국내외 특허데이터를 수집한 후 키워드 네트워크 분석과 IPC 코드 분석을 통해 기술 구조와 핵심 키워드를 도출하였으며, 'Voltage', 'System', 'Converter', 'Control' 등이 핵심 기술군으로 나타났다. 특히 IPC 트렌드 분석 결과 최근에는 보호 및 제어 중심의 지능형 시스템 기술이 부상하고 있음을 확인하였고, 이는 HVDC 기술이 전통적 송전 중심에서 통합 운영과 디지털 기반 시스템으로 진화하고 있음을 보여준다. 본 연구는 향후 HVDC 국내 기술개발 방향 설정과 글로벌 기술경쟁력 확보를 위한 전략 수립에 있어 기초자 료로 활용될 수 있을 것으로 기대된다.

우리나라 헌법 제107조 제3항은 재판의 전심절차로서 행정심판을 할 수 있 으며 절차는 법률로 정하되, 사법절차가 준용되어야 한다고 규정한다. 그리고 행정심판법 제4조 제1항에서는 사안의 전문성과 특수성이 인정되면 필요에 따 라 개별법이 정한 특례절차에 따라 심판을 할 수 있도록 규정하고 있다. 이러 한 특례절차에 따른 행정심판을 특별행정심판이라 하는데, 해양안전심판, 특허 심판 및 조세심판 등이 있다. 특별행정심판 중에서도 해양안전심판은 해양사고의 원인규명재결뿐만 아니 라 해기사 등에 대한 징계재결까지도 심판의 결과로 도출하는 특별한 형태의 행정심판으로서 구술변론주의, 대심주의 및 조사관의 청구독점주의 등을 채택 하고 있다. 그러나 조사관은 해양사고관련자를 조사하는 권한을 가지고 있어 해양사고관련자와 대등한 입장이라 보기 어렵다. 그러므로 상대적 약자인 해양 사고관련자의 정당한 권리구제와 방어권을 보장하기 위해서는 심판변론인 제 도의 적극적 활용이 무엇보다 중요하다. 이 연구에서는 해양사고심판의 심판변론인제도를 다양한 측면에서 살펴보 고, 다른 특별행정심판인 특허심판과 조세심판 제도와 비교·분석하여 해양안전 심판의 심판변론인제도에 대한 문제점을 도출하고 개선방안을 제안하고자 한다.

The era of logistics 4.0 in which new technologies are applied to existing traditional logistics management has approached. It is developing based on the convergence between various technologies, and R&D are being conducted worldwide to build smart logistics by synchronizing various services with the logistics industry. Therefore, this study proposes a methodology and technology strategy that can achieve trend analysis using patent analysis and promote the development of the domestic smart logistics industry based on this. Based on the preceding research, eight key technology fields related to smart logistics were selected, and technology trends were derived through LDA techniques. After that, for the development of the domestic logistics industry, the strategy of the domestic smart logistics industry was derived based on analysis including technology capabilities. It proposed a growth plan in the field of big data and IoT in terms of artificial intelligence, autonomous vehicles, and marketability. This study confirmed smart logistics technologies by using LDA and quantitative indicators expressing the market and technology of patents in literature analysis-oriented research that mainly focused on trend analysis. It is expected that this method can also be applied to emerging logistics technologies in the future.

본 연구에서는 해양공간 통합관리 수단의 지원책으로 활용되는 해양공간 정책 시뮬레이터 기술에 대한 한국, 중국, 일본, 미국, 유럽 등 주요 5개국에 대한 정량분석을 위한 유효특허 1,474건을 도출하고, 연도별, 국가별 특허출원 동향 및 워드 클라우드 분석을 통해 국내 기술 경쟁력 및 국내·외 기술 트렌드를 파악하였다. 분석 결과 해양공간 정책 시뮬레이터 기술의 경우 중국(1,254건, 85.1%) 주도의 특허출원이 활발하게 이루어지고 있으며, 세부 기술별로는 어업환경 변화예측 및 활용 시뮬레이터(AC)가 392건(26.6%)으로 가장 높은 것 으로 나타난다. 핵심 키워드 변화를 통해 최근에는 다중 데이터의 수집과 데이터의 탐지, 예측, 평가 등으로 기술 트렌드가 이루어지고 있 음을 확인하였으며, 중국 주도의 시장 독과점 및 선점에 대비하기 위해 주변 기술에 대한 특허출원 고려 및 표준화 선점 등의 연계 전략 을 통한 대비와 정부 차원의 해양공간 정책 시뮬레이터 기술 연구개발에 대한 적극적인 정책적 지원이 필요함을 진단하였다.

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

As markets and industries continue to evolve rapidly, technology opportunity discovery (TOD) has become critical to a firm's survival. From a common consensus that TOD based on a firm’s capabilities is a valuable method for small and medium-sized enterprises (SMEs) and reduces the risk of failure in technology development, studies for TOD based on a firm’s capabilities have been actively conducted. However, previous studies mainly focused on a firm's technological capabilities and rarely on business capabilities. Since discovered technologies can create market value when utilized in a firm's business, a firm’s current business capabilities should be considered in discovering technology opportunities. In this context, this study proposes a TOD method that considers both a firm's business and technological capabilities. To this end, this study uses patent data, which represents the firm's technological capabilities, and trademark data, which represents the firm's business capabilities. The proposed method comprises four steps: 1) Constructing firm technology and business capability matrices using patent classification codes and trademark similarity group codes; 2) Transforming the capability matrices to preference matrices using the fuzzy function; 3) Identifying a target firm’s candidate technology opportunities using the collaborative filtering algorithm; 4) Recommending technology opportunities using a portfolio map constructed based on technology similarity and applicability indices. A case study is conducted on a security firm to determine the validity of the proposed method. The proposed method can assist SMEs that face resource constraints in identifying technology opportunities. Further, it can be used by firms that do not possess patents since the proposed method uncovers technology opportunities based on business capabilities.

본 연구의 목적은 재료분야 국내 공동특허의 공동 출원인 정보를 이용하여 연구협력 네트워크의 구조, 특징, 진화를 탐구하는 것이다. 이를 위해 재료 기술분야(금속, 세라믹, 고분자 등 6개 기술분야) 및 혁신주체(산업계, 학계, 연구계)의 네트워크 구조 및 동태를 정량적으로 분석하며, 2010년∼2021년까지 한국의 공동특허 데이터를 활용하여 소셜 네트워크 분석(SNA)을 사용한다. 분석결과, 재료분야는 세부기술별로 네트워크의 차별점이 존재하며, 산업계, 학계, 연구계 등 혁신주체별 협력 강도의 명백한 단계별 특성을 가진다. 연구협력 네트워크의 규모는 점차 확장되어 ‘작은 세계’ 구조를 보여주고 있다. 본 연구를 통해 재료 정책 관점에서 지금까지 시행된 재료분야 산학연 협력 정책의 효과를 파악하는데 정책적 시사점을 제공함과 동시에, 보다 효과적인 재료 혁신주체 간의 네트워크를 구축하기 위한 근거 기반의 정책 수립에 도움이 될 수 있다.

인공지능은 4차 산업혁명의 프레임이 소개된 이후 점차 보편적인 기술로 자리를 잡아가고 있으며, 인공지능 관련 특허 출원도 크게 증가하고 있다. 최근에는 특허 생태계가 출원 건수 위주의 양적 경쟁에서 고품질의 특허 확보라는 질적 경쟁으로 패러다임이 변화되면서, 저품질 특허로 인한 비용 손실에 관심이 높아지고 있다. 이러한 배경으로 본 연구에서는 머신러닝과 Doc2Vec 알고리즘을 활용하여 특허 품질을 예측하는 방법을 제안하고자 한다. 본 연구를 위해 WIPO에서 정의한 CPC 코드를 활용하여 미국 특허청(USPTO)에 등록된 인공지능 관련 특허 데이터를 추출하였고, 이를 통해 정형 데이터 기반 19개 변수, 비정형 데이터 기반 7개 변수를 개발하였다. 특히, 새롭게 제안하는 Doc2Vec 알고리즘을 이용한 제목과 초록 텍스트 유사도 변수는 고품질 특허를 예측하는데 영향을 미칠 것으로 판단된다. 이에 유사도 변수의 효과를 확인하기 위해 유사도 변수를 포함한 앙상블 기반 머신러닝 모델과 포함하지 않은 모델을 개발하여 비교하였다. 실험 결과, 유사도 변수를 포함한 모델이 AUC 0.013, f1-score 0.025가 높게 나타나 더 우수한 성능을 보였다. 이는 유사도 변수가 고품질 특허 예측에 기여한다는 것을 시사한다. 또한, SHAP을 이용하여 블랙박스 형태의 머신러닝 변수 영향도를 설명하였다. 본 연구를 통해 핵심 기술 분야인 인공지능과 같은 영역에서 특허의 품질을 예측하고, 고품질 특허 개발을 장려함으로써 사회적 가치를 실현하는 데 기여할 수 있을 것으로 기대한다.

Recently, the market competition has been fiercer due to the acceleration of technological change and the launch of intelligent products. In this situation, technology cooperation activities through networks rather than independent technological innovation activities of a single company or institution are recognized as a crucial strategy to gain competitiveness. Technology cooperation can take various forms depending on the target technology, and researchers have conducted performance analyses of technology cooperation types. However, there have not been data-based quantitative studies on the types and trends of technology cooperation for the target technology. In this paper, we explored the difference between the technology cooperation types by technology and time using the formal concept analysis method and co-patent information. In particular, the proposed methodology has been verified through the case study of electric vehicles, and it is intended to suggest the direction of technological cooperation according to specific technologies and cooperation targets in the future

In this review, we examine the latest technological developments in the utilization of truffles, a gourmet ingredient reputed to be one of the "world's three greatest delicacies," considering changing global consumption trends. Global demand for truffles is expected to increase steadily, with an average annual growth rate of 8.9% from 2023 to 2030. As truffles are expensive, the demand for truffles is expected to be concentrated in developed countries such as the United States, European countries, and Japan. In Korea, truffles are utilized in various industries, including food, functional foods, and cosmetics. Korean consumer demand for truffles has consistently remained high since 2019, and truffle products have been performing well in the market. Consequently, there exists substantial potential demand for newly developed truffle-related products and technologies. This review aims to provide objective research information through the systematic analysis of patent applications in Korea and internationally, focusing on technologies involving truffles, and can aid in setting directions for research and development.

The importance of biocomposites has increased owing to the changes in global consumption trends and rapid climate change. Technologies using mushroom mycelium cultivation, and molding methods for mycelial application have gained attention as potential strategies for producing eco-friendly composites. Currently, mushroom mycelia are used as raw materials for food and cosmetics; however, research on their utilization as biocomposite materials is limited. Therefore, the potential for the development of mushroom mycelium-related products and technologies is high. This review analyzes the domestic and international patent application trends related to the technologies for composite (packaging, insulation, adhesives, and leather) and food (substitute for meat) materials using mushroom mycelium, as an eco-friendly biocomposite material, to provide objective patent information that can further research and development (R&D) in this field.

The increasing number of technology transfers from public research institutes in Korea has led to a growing demand for patent recommendation platforms for SMEs. This is because selecting the right technology for commercialization is a critical factor in business success. This study developed a patent recommendation system that uses technology transfer data from the past 10 years to recommend patents that are suitable for SMEs. The system was developed in three stages. First, an item-based collaborative filtering system was developed to recommend patents based on the similarities between the patents that SMEs have previously transferred. Next, a content-based recommendation system based on TF-IDF was developed to analyze patent names and recommend patents with high similarity. Finally, a hybrid system was developed that combines the strengths of both recommendation systems. The experimental results showed that the hybrid system was able to recommend patents that were both similar and relevant to the SMEs' interests. This suggests that the system can be a valuable tool for SMEs that are looking to acquire new technologies.