• Journal of Digital Convergence
• /
• v.12 no.5
• /
• pp.115-123
• /
• 2014

Patent information analysis has been carried out for technological capability analysis of competitors relating to next generation mobile communication. Various analysis methods, such as applicant analysis, technology classification analysis, indicator analysis and the like have been utilized as a method of analyzing patent information. As a first step for the technological capability analysis of competitors, applicants having high patent activity(PA) were selected, and as a second step therefor, technology classifications showing high technological independence (TI) were selected. Furthermore, portfolios for technology classifications showing high technological independence in the patents of main applicants having high patent activity by matching results the first and second steps together were prepared. Through such a process, portfolios for important technologies which have been concentrically researched by competitors could be analyzed. Accordingly, the present analysis results will help to carry out strategic R&D management, such as the establishment of company R&D plans and patent strategies.

• Bulletin of the Korean Mathematical Society
• /
• v.35 no.3
• /
• pp.547-557
• /
• 1998

In this paper, we study submanifolds in the Euclidean space with parallel normal mean curvature vectorand special quadric representation. Especially we give a complete classification result relative to surfaces satisfying these conditions.

• International Journal of Advanced Culture Technology
• /
• v.8 no.1
• /
• pp.165-172
• /
• 2020

Industrial Revolution means the improvement of productivity through technological innovation and has been a driving force of the whole change of economic system and social structure as the characteristic of technology as the tool of this productivity has changed. Since the first industrial revolution of the 18th century, productivity efficiency has been advanced through three industrial revolutions so far, and this fourth industrial revolution is expected to bring about another revolution of production. In this study, the demand for the introduction of artificial intelligence(AI) technology has been increasing in various business fields due to the rapid development of ICT technology, and the classification of HS(harmonized commodity description and coding system) items has been decided using artificial intelligence technology, which is the core of the fourth industrial revolution. And it is enough to construct HS classification system based on AI technology using inference and deep learning. Performing the HS item classification is not an easy task. Implementation of item classification system using artificial intelligence technology to analyze information of HS item classification which is performed manually by the current person more accurately and without any mistake, And the customs administrations, customs offices, and customs agencies, it is expected to be highly utilized in the innovation of trade practice and the customs administration innovation FTA origin agent.

• Journal of the Korean Society of Safety
• /
• v.32 no.5
• /
• pp.88-95
• /
• 2017

As the safety fields are expanding to a variety of industrial fields, safety technology has been developed by convergence between industrial safety fields such as mechanics, ergonomics, electronics, chemistry, construction, and information science. As the technology convergence is facilitating recently advanced safety technology, it is important to explore the trends of safety technology for understanding which industrial technologies have been integrated thus far. For studying the trends of technology, the patent is considered one of the useful sources that has provided the ample information of new technology. The patent has been also used to identify the patterns of technology convergence through various quantitative methods. In this respect, this study aims to identify the convergence patterns and fields of safety technology using association rule mining(ARM)-based patent co-classification(co-class) analysis. The patent co-class data is especially useful for constructing convergence network between technological fields. Through linkages between technological fields, the core and hub classes of convergence network are explored to provide insight into the fields of safety technology. As the representative method for analyzing patent co-class network, the ARM is used to find the likelihood of co-occurrence of patent classes and the ARM network is presented to visualize the convergence network of safety technology. As a result, we find three major convergence fields of safety technology: working safety, medical safety, and vehicle safety.

• Journal of Technology Innovation
• /
• v.21 no.2
• /
• pp.25-56
• /
• 2013

As science and technology are emphasized as national competitiveness, major nations designate new growth engine industry and establish the effective investment and the development strategy to enhance industrial development and competitiveness through science and technology. New industrial sectors such as Biotechnology and renewable energy have been spot lighted as major new growth engines and this competitive situation is getting fiercer. Universities and research institutions in each country selected and announced the future promising technological field which will produce ripple effect in the future on a regular basis. In Korea, various research institutions continue to select and announce the promising technological fields. In this study, we would like to study the method to derive the promising technological field in the field of biotechnology spotlighted as a new growth engine by utilizing patent information. We would like to derive the major technological field by collecting domestic and international patents in the field of biotechnology using IPC code based technological classification and identifying bio technological trends utilizing text mining method for analysis of technological development trends with patents. Patent contour of US and Korea is compared and analyzed through analysis of text mining to derive the general technological development field in the field of biotechnology. After that, we would like to investigate research theme of promising biotechnology focused technological development through details on technological trends through in-depth analysis about technological field which draws interest more and more in Korea and other countries.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.7
• /
• pp.2633-2648
• /
• 2015

The problem of visual words' synonymy and ambiguity always exist in the conventional bag of visual words (BoVW) model based object category methods. Besides, the noisy visual words, so-called "visual stop-words" will degrade the semantic resolution of visual dictionary. In view of this, a novel bag of visual words method based on PLSA and chi-square model for object category is proposed. Firstly, Probabilistic Latent Semantic Analysis (PLSA) is used to analyze the semantic co-occurrence probability of visual words, infer the latent semantic topics in images, and get the latent topic distributions induced by the words. Secondly, the KL divergence is adopt to measure the semantic distance between visual words, which can get semantically related homoionym. Then, adaptive soft-assignment strategy is combined to realize the soft mapping between SIFT features and some homoionym. Finally, the chi-square model is introduced to eliminate the "visual stop-words" and reconstruct the visual vocabulary histograms. Moreover, SVM (Support Vector Machine) is applied to accomplish object classification. Experimental results indicated that the synonymy and ambiguity problems of visual words can be overcome effectively. The distinguish ability of visual semantic resolution as well as the object classification performance are substantially boosted compared with the traditional methods.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.3
• /
• pp.471-481
• /
• 2023

Digital twin is considered as a key technology of industry 4.0, thus being essential for the future of industrial production. Despite the significance, a systematic analysis of its technological landscape is lacking. This study aims to investigate the technological development trends and newly emerging technological convergence opportunities in the domain of digital twin by exploiting patent information derived from U SPTO. For this purpose, this study visualized and predicted the convergence dynamics among patent classification codes by adopting patent co-classification analysis and link prediction approach. The findings show that the number of digital twin-related patent applications has increased significantly since 2018. The CPC code G06F showed the highest eigenvector centrality, while G05B was characterized by highest betweenness centrality. According to the predictive model, 41 novel links were revealed, acting as potential technology convergence opportunities. These links were then categorized into 11 different domains. The most dominant category was "digital data processing and artificial intelligence", which could play a foundational role in the diffusion of digital twin technology. The presence of digital twin technology is dominant in manufacturing, but its applications are expected to expand, including "climate change", "healthcare" and "aerospace engineering". The derived insights can support R&D managers and policy makers in formulating R&D strategies and directing future R&D investment decisions.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.4
• /
• pp.1-14
• /
• 2023

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.

• The Journal of Information Systems
• /
• v.6 no.1
• /
• pp.181-221
• /
• 1997

In order to provide effective information services in a province, we should first select vendors who enable to meet end-users' needs and develop information services for the sake of end-users. Cases, policies, technological and legislative issues in information services have been researched well. But no research has been done on potential information services in the future and their classification. In this study, based on literature survey, future information services are gathered, described, and classified with respect to the needs of end-users, and finally a framework for the classification of information services is developed. This framework can be used as a criterion to select, with a priority, information services to be provided in province through the information super highway. The framework will contribute to accomplishing the effective use of information resources in the province, and eventually balancing the level of information utilization between provinces.

• New & Renewable Energy
• /
• v.7 no.1
• /
• pp.36-44
• /
• 2011

Technology is developed from the efficient interaction with other technology files while building up its own research field. This study analyzes the structure of solar cell research area and describes its paths of the technology development in terms of interdisciplinary diversity using the Co-Classification method during 1979-2009. As a results, 1,380 studies are determined as the interdisciplinary among the 2,605 studies. It shows that 52.98% of the solar cell researches have interdisciplinary relationships with two or more research fields. In addition, we show that the research area of solar cell technology is composed by Material Science, Multidisciplinary and Energy & Fuel, Physics, Applied, Chemistry, Physical from the Co-Classification matrix and network analysis. It means the complexity of the technological knowledge production increased with the concept of interdisciplinary. The results can be used for the planning of the efficient solar cell technology development.