Analysis Of Technological Trends Research Articles

특허정보를 활용한 국방 R&D 기술추세 분석

Korea reached the world’s highest level in terms of national R&D investment, but analysis has been conducted mainly through qualitative methods such as literature research and Delphi techniques rather than objective analysis of technology trends in the R&D planning stage by technology sector. In the case of the defense field, in particular, few studies have been conducted on quantitative trend analysis due to security and closeness, and existing previous studies have been analyzed limited to specific technologies. Therefore, this study attempted to improve the efficiency of analysis by applying patent data containing technical information to defense technology analysis using big data analysis methods and processes for quantitative analysis of technology trends. To carry out this, after collecting patent data from the Agency for Defense Development for 20 years, major R&D fields were derived using topic modeling techniques, and based on the results, the trend of technological change over time was examined. In addition, in order to find out the interrelationship between the derived topics, the association rule mining(ARM) was performed to identify which fields are being studied together and visualize the connection network. It is expected that the technology trends and analysis methods presented through this study will be effectively used to establish R&D technology policies.

Analysis of Digital Twin Technology Trends Related to Geoscience and Mineral Resources after the Korean New Deal Policy in 2020

Analysis of Digital Twin Technology Trends Related to Geoscience and Mineral Resources after the Korean New Deal Policy in 2020

An Intelligent Mechanism to Automatically Discover Emerging Technology Trends: Exploring Regulatory Technology

Technology trend analysis uses data relevant to historical performance and extrapolates it to estimate and assess the future potential of technology. Such analysis is used to analyze emerging technologies or predict the growing markets that influence the resulting social or economic development to assist in effective decision-making. Traditional trend analysis methods are time-consuming and require considerable labor. Moreover, the implemented processes may largely rely on the specific knowledge of the domain experts. With the advancement in the areas of science and technology, emerging cross-domain trends have received growing attention for its considerable influence on society and the economy. Consequently, emerging cross-domain predictions that combine or complement various technologies or integrate with diverse disciplines may be more critical than other tools and applications in the same domain. This study uses a design science research methodology, a text mining technique, and social network analysis (SNA) to analyze the development trends concerning the presentation of the product or service information on a company's website. This study applies regulatory technology (RegTech) as a case to analyze and justify the emerging cross-disciplinary trend. Furthermore, an experimental study is conducted using the Google search engine to verify and validate the proposed research mechanism at the end of this study. The study results reveal that, compared with Google Trends and Google Correlate, the research mechanism proposed in this study is more illustrative, feasible, and promising because it reduces noise and avoids the additional time and effort required to perform a further in-depth exploration to obtain the information.

Reconsidering Dale’s Cone: Towards the development of a 21st century “Cone of Experience” to address social justice issues

With the overarching goal of understanding the full scope of recent technology trends, this position paper developed an initial framework of possible instructional technologies and their potential impact on social justice issues. To construct this framework, an analysis of technology trends during the last 11 years was conducted. Our emerging framework includes 11 primary technology trends categories. In addition to describing this framework, specific social justice instructional activities in utilizing Molenda and Subramony’s (2021) communication configurations, as well as elements of the Cone of Experience described by Dale (1969), are proposed.

Research and Technology Trend Analysis by Big Data-Based Smart Livestock Technology: a Review

Research and Technology Trend Analysis by Big Data-Based Smart Livestock Technology: a Review

Análisis metodológico de los estudios prospectivos que exploran el futuro de la bioeconomía

La innovación basada en ciencias de la vida aspira a hacer frente a las metas ambientales y de desarrollo. En este contexto nos proponemos caracterizar las metodologías para explorar el futuro de la bioeconomía. En virtud de que la prospectiva tecnológica incorpora diversas herramientas para hacer frente a la complejidad tecnológica y social, nos interesa identificar cuáles han predominado en la investigación académica y cómo se han complementado para explorar el desarrollo del sector y diseñar escenarios de futuro. Método: Condujimos una investigación documental, basada en revistas académicas indizadas en Scopus. Emprendimos un análisis bibliométrico sobre una base de 31 artículos de investigación publicados entre 2015 y 2019. Continuamos con una revisión de la literatura con el propósito de codificar variables sobre el alcance y la metodología, a fin de estar en condiciones de comparar nuestros resultados con las mejores prácticas desprendidas del Diamante de Popper. Clasificamos las herramientas de prospectiva encontradas conforme a su dependencia de fuentes de “evidencia”, “experticia”, “interacción social” y “creatividad”. Finalmente, realizamos un análisis de la red de complementariedades entre enfoques y herramientas en el programa Gephi 0.9.2. Resultados: Con relación al alcance, predominó la exploración de futuros con escenarios hacia el 2030 (33%) y 2050 (5%), con preferencia por la escala nacional (43%), por encima de la internacional (38%) y subnacional (20%), en temas relacionados con la factibilidad ambiental y económica de la energía y la biomasa, y en menor medida sobre el análisis de la bioeconomía en su conjunto. En términos de enfoque metodológico, prevalecieron las herramientas basadas en evidencia cuantitativa (71%) y en la opinión de expertos (21%); marginando la incorporación de la opinión de diversos actores sociales (8%) y el uso de herramientas basadas en creatividad (0%). De un total de 33 herramientas de uso común en la práctica prospectiva, se emplearon 11, optando por la incorporación de 1 a 2 por ejercicio (1.3 en promedio). Conclusión: Nuestros hallazgos se distinguen de estudios previos sobre ejercicios prospectivos que habían documentado la escasa relevancia del sector de estudio en la elección de las herramientas y mostraban la prevalencia de herramientas cualitativas. Por otro lado, corroboran otros estudios que han comenzado a documentar el surgimiento de nuevos campos de aplicación y nuevas combinaciones de herramientas. Para el sector de bioeconomía, consideramos que la cantidad de enfoques, y el nivel de combinación de herramientas empleadas, resulta limitado para explorar la transición hacia un sistema económico sustentable apoyado por la innovación en ciencias de la vida. El análisis de tendencias tecnológicas necesita retroalimentarse de la opinión de actores sociales clave e incorporar elementos creativos en correspondencia con la multiplicidad de factores que explican la adopción de nuevas tecnologías por amplios colectivos sociales.

Sensitivity of light duty vehicle tailpipe emission rates from simplified portable emission measurement systems to variation in engine volumetric efficiency

ABSTRACT Light-duty gasoline vehicle (LDGV) tailpipe emission rates can be quantified based on pollutant concentrations measured using portable emission measurement systems (PEMS). Emission rates depend on exhaust flow. For simplified and micro-PEMS, exhaust flow is inferred from engine mass air flow (MAF) and air-to-fuel ratio. For many LDGVs, MAF is broadcast via the on-board diagnostic (OBD) interface. For some vehicles, only indirect indicators of MAF are broadcast. In such cases, MAF can be estimated using the speed-density method (SDM). The SDM requires an estimate of the engine volumetric efficiency (VE), which is the ratio of actual to theoretical MAF. VE is affected by intra-vehicle variability in the engine load and inter-vehicle variability in engine characteristics (e.g., the type of valvetrain). The suitability of SDM-based estimates of MAF in conjunction with simplified and micro-PEMS has not been adequately evaluated. Therefore, the objectives are to: (1) quantify VE accounting for intra- and inter-vehicle variability; and (2) evaluate the accuracy of SDM-based vehicle emission rate estimation approaches. Seventy-seven naturally-aspirated LDGVs were measured using PEMS. For each vehicle, VE was estimated using three approaches: (1) constant VE calibrated to actual fuel use; (2) average estimates of VE for Vehicle Specific Power modes imputed from OBD data; and (3) modeled VE using multilinear regression (MLR). The MLR models were developed based on engine load and engine characteristics. The best model was selected based on various statistical diagnostics. When engines were under load, variability in VE was most sensitive to variations in engine load. During idling, VE differed between engines depending on engine characteristics. The constant and modeled VE estimation approaches enable the accurate estimation of microscale and mesoscale emission rates, with errors typically within ±10% compared to values imputed from OBD data. Thus, accurate emission rates can be obtained from simplified and micro-PEMS. Implications: Simplified and micro portable emission measurement systems (PEMS) enable widespread measurement of vehicle exhaust emission. As a cost saving measure, they estimate exhaust flow indirectly rather than via measurement, typically based on engine mass air flow (MAF). For some vehicles, MAF is not reported by the on-board diagnostic (OBD) system but can be inferred from other reported variables and volumetric efficiency (VE). However, VE is typically proprietary. Methods demonstrated here for estimating VE enable accurate quantification of emission rates, thereby enabling use of these PEMS for policy-relevant applications such as technology assessments, trends analysis, and emissions inventories.

Reconsidering Dale’s Cone: Towards the Development of a 21st Century “Cone of Experience” to Address Social Justice Issues

With the overarching goal of understanding the full scope of recent technology trends, this position paper developed an initial framework of possible instructional technologies and their potential impact on social justice issues. To construct this framework, an analysis of technology trends during the last 11 years was conducted. Our emerging framework includes 11 primary technology trends categories. In addition to describing this framework, specific social justice instructional activities in utilizing Molenda and Subramony’s (2021) communication configurations, as well as elements of the Cone of Experience described by Dale (1969), are proposed.

Grinding and fine finishing of future automotive powertrain components

The automotive industry is undergoing a major transformation driven by regulations and a fast-paced electrification. A critical analysis of technological trends and associated requirements for major automotive powertrain components is carried out in close collaboration with industry – covering the perspectives of OEMs, suppliers, and machine builders. The main focus is to review the state of the art with regard to grinding, dressing, texturing and fine-finishing technologies. A survey of research papers and patents is accompanied by case studies that provide further insights into the production value chain. Finally, key industrial and research challenges are summarized.

An intelligent patent recommender adopting machine learning approach for natural language processing: A case study for smart machinery technology mining

Recommendation systems are widely applied in many fields, such as online customized product searches and customer-centric advertisements. This research develops the methodology for a patent recommender to discover semantically relevant patents for further technology mining and trend analysis. The proposed recommender adopts machine learning (ML) algorithms for natural language processing (NLP) to represent patent documents in vector space and to enable semantic analyses of the patent documents. The ML approach of neural network (NN) language models, trained by domain patent documents (text) as a training set, convert patent documents into vectors and, thus, can identify semantically similar patents using document similarity measures. In particular, the proposed recommender is deployed to in-depth case studies for advanced patent recommendations. The case domain of smart machinery is used to better enable smart manufacturing by incorporating innovative technologies, such as intelligent sensors, intelligent controllers, and intelligent decision making. The research uses six sub-domains in smart machinery technologies as the case studies to verify the superior accuracy and efficacy of the recommender system and methodologies.

Determining future professions and competencies of health workers

Abstract Background Constantly growing needs and challenges for the healthcare sector lead to the development of new technologies and new approaches to health promotion, which, in turn, leads to the emergence of new needs of new professions (NPs) and new competencies (NCs). Accordingly, timely forecasting of NPs and NCs of health workers (HWs) is of high relevance, since it is necessary to create conditions for the timely training of HWs with NPs and NCs Methods At the first stage, we carried out an analysis of technological trends and challenges in modern healthcare to identify potential NPs and NCs of HWs that may be required in the future. Then, the selection of the most demanded NPs and NCs was carried out on the basis of a study of a 2-round Delphi study - 196 experts selected according to the principle of “Side of the World” - from 5 organizations in 5 regions of the Republic of Kazakhstan (north, south, west, east, center). Then we made prioritization of NPs and NCs, which will be in demand in the next 10 years for the health system. Results Based on our research, a list of the following NPs was determined: IT specialist in medicine, bioethics, telemedicine physician, molecular nutritionist, clinical bioinformatics, consultant for healthy old age, expert in personalized medicine, engineer for organs and tissues, life style strategist, operator of medical robots, ergotherapist, kinesiotherapist, biopharmacologist, medical journalist, architect of medical equipment, developer of cyber prosthetics and implants. A list of NCs that will be in demand in the coming years for HWs was also determined: competencies in the fields of personalized and preventive medicine, robotic medicine, IT technology, logistics of health services, biotechnology, nanomedicine, online counseling. Conclusions The results of our study indicate the need to consolidate selected professions in the sectoral qualifications system, as well as the need to launch training programs for these NPs and NCs. Key messages An analysis of technological trends in the healthcare system and Delphi research allowed us to formulate a list of NPs and NCs. It is necessary to create a system of support and promotion of NPs and NCs to improve the quality of health services.

Analysis of Technological Trends and Technological Portfolio of Unmanned Aerial Vehicle

Unmanned aerial vehicles (UAVs) are predicted to be the most dynamic growth sector of the world aerospace market this decade. This technology is swiftly strengthening its presence in multiple fields of human life. In the global aerospace industry, UAVs have become an essential means of securing growth and competitiveness. The investment in UAVs is estimated at billions of dollars in developed countries. However, despite the rapid growth of UAVs, few studies have classified UAV technologies into detailed technologies, or analyzed the technology development trends of UAVs. We used the latent Dirichlet allocation (LDA) method of topic modeling and network analysis to analyze the technological trends and technological portfolio of UAVs. The UAV patents were collected from the Korea Intellectual Property Rights Information Service. Analyzing the results shows that the most popular topics are communication technology (34.1%), power supply (19.5%) and navigation system (17.6%). The technological portfolio of a UAV is constituted of three groups: control system, operation system and device. This study is expected to be guidelines for developers and policy-makers on UAVs.

Technology Topic Mining and Trend Analysis from the Perspective of Industrial Chain Combined with K-Means and LDA——Taking Virtual Reality Technology as an Example

Technology Topic Mining and Trend Analysis from the Perspective of Industrial Chain Combined with K-Means and LDA——Taking Virtual Reality Technology as an Example

Discovering Associations Among Technologies Using Neural Networks for Tech-Mining

In both public and private sectors, critical technology-based tasks, such as innovation, forecasting, and road-mapping, are faced with unmanageable complexity due to the ever-expanding web of technologies which can range into thousands. This context cannot be easily handled manually or with efficient speed. However, more precise and insightful answers are expected. These answers are the fundamental challenge addressed by tech-mining. For tech-mining, discovering the associations among them is a critical task. These associations are used to form a weighted directed graph of technologies called “association tech-graph” which is used for technology development, trend analysis, policymaking, strategic planning, and innovation. In this article, we present a novel method to build an artificial intelligence (AI) agent for automatic association discovery among technologies in a way that matches the quality of the human experts. To this end, neural network-based word embedding methods are exploited to represent technology terms as vectors, and their associations are calculated using similarity measures. To increase the accuracy of the vectors, several crawlers are built to acquire more appropriate training data. Furthermore, we introduce a validation method to measure the accuracy of the AI agent compared to human intelligence, which allows us to discuss the drawbacks of both approaches.

Word2vec-based latent semantic analysis (W2V-LSA) for topic modeling: A study on blockchain technology trend analysis

Blockchain has become one of the core technologies in Industry 4.0. To help decision-makers establish action plans based on blockchain, it is an urgent task to analyze trends in blockchain technology. However, most of existing studies on blockchain trend analysis are based on effort demanding full-text investigation or traditional bibliometric methods whose study scope is limited to a frequency-based statistical analysis. Therefore, in this paper, we propose a new topic modeling method called Word2vec-based Latent Semantic Analysis (W2V-LSA), which is based on Word2vec and Spherical k-means clustering to better capture and represent the context of a corpus. We then used W2V-LSA to perform an annual trend analysis of blockchain research by country and time for 231 abstracts of blockchain-related papers published over the past five years. The performance of the proposed algorithm was compared to Probabilistic LSA, one of the common topic modeling techniques. The experimental results confirmed the usefulness of W2V-LSA in terms of the accuracy and diversity of topics by quantitative and qualitative evaluation. The proposed method can be a competitive alternative for better topic modeling to provide direction for future research in technology trend analysis and it is applicable to various expert systems related to text mining.

Analysis of Technology Trends and Technology Covergence for Parkinson's Disease Therapeutics : Based on Global Patent Information

Analysis of Technology Trends and Technology Covergence for Parkinson's Disease Therapeutics : Based on Global Patent Information

ПРЕДСКАЗАТЕЛЬНОЕ МОДЕЛИРОВАНИЕ ТРЕНДОВ ТЕХНОЛОГИЧЕСКОГО РАЗВИТИЯ

In the work, the problem of forecasting technological development trends was considered. A review of the sources of the global patent space, an analysis of technological development trends, a survey of data sources for training the neural network were carried out. Existing data mining techniques were analyzed for more accurate and faster forecasting. A module for predictive modeling of trends in technological development was developed, algorithms for the module for predictive modeling of trends in technological development were described.

Development of Disaster Safety Technologies Through Analysis of Safety Service Trends in Disaster Prevention

The objectives of this study are to identify the possibility of new, future, and complex disasters resulting from environmental changes and corresponding requirements through the analysis of technology trends and safety services for disaster prevention, and to provide the basic data for the development of safety service technologies for people's safety and security. The R&D trends related to disaster safety are technology developments related to 1) search for future and new disasters, 2) integrated management of disasters and safety technology standards, 3) national continuity of operation management for disaster prevention, 4) disaster response, relief, and recovery, and 5) safety and security of vulnerable population. A review of various international cases reveals that appropriate technology development and policy support are needed, and that the role of disaster safety control tower and disaster management institutions is important. Also, integrated safety management technologies for new and future disasters, and development of technologies for large-scale disasters are needed, as is development of technologies for protecting people, including those vulnerable to paralysis of national infrastructure facilities. Keywords: Disaster Prevention, Safety Service Technology, Control Tower, Disaster Management, New and Future Disasters

Mining the Automotive Industry: A Network Analysis of Corporate Positioning and Technological Trends

The digital transformation is driving revolutionary innovations and new market entrants threaten established sectors of the economy such as the automotive industry. Following the need for monitoring shifting industries, we present a network-centered analysis of car manufacturer web pages. Solely exploiting publicly-available information, we construct large networks from web pages and hyperlinks. The network properties disclose the internal corporate positioning of the three largest automotive manufacturers, Toyota, Volkswagen and Hyundai with respect to innovative trends and their international outlook. We tag web pages concerned with topics like e-mobility & environment or autonomous driving, and investigate their relevance in the network. Toyota and Hyundai are concerned with e-mobility throughout large parts of their web page network; Volkswagen devotes more specialized sections to it, but reveals a strong focus on autonomous driving. Sentiment analysis on individual web pages uncovers a relationship between page linking and use of positive language, particularly with respect to innovative trends. Web pages of the same country domain form clusters of different size in the network that reveal strong correlations with sales market orientation. Our approach is highly transparent, reproducible and data driven, and could be used to gain complementary insights into innovative strategies of firms and competitive landscapes.

SMALL HYDROPOWER PLANTS AS A PART OF ELECTRIC POWER INDUSTRY AND ENERGY MARKET OF UKRAINE

Globalization and sustainable development necessitate joint analysis of technological and environmental trends in energy development taking into account current economic and legal provisions. Based on synthesis of the current state of Ukrainian electric power system in general and hydropower in particular, there have been underscored the importance of comprehensive approach in identifying the key tasks of building the pathway of further electric power industry development. The authors provide the characteristics of today’s organizational and technological structure of the electric power system, including the legal provisions regulating its activity. As currently there are significant legislative changes, particular attention was paid to the review of electricity market. Features of the new liberalized electricity market have been determined in comparison with the current market, and also in connection with renewable energy characteristics. Thus, amendments introduced by the new Law “On electricity market” to the green tariff policy have been detailed with the regard to incentive mechanism for development of renewable energy and liability of electricity producers operating under Green Tariff for imbalances. The article focuses on the analysis of the state and growth potential of small hydropower. Еconomic incentives are systematized according to the current legislation. Also, here is presented the potential for possible growth of small hydropower, namely, quantitative result of the exploration of the technical potential of hydropower resources of small rivers. There have been identified a number of barriers and impediments to the construction of small HPPs. Environmental restrictions to the construction of small hydropower stations have been formulated according to the accurate analysis of various branches of national legislation such as the Land Code, the Water Code, the Law “On the Nature Reserve Fund of Ukraine”, etc., as well as valid ratified documents and other key soft-low instruments at the international level. Additionally, provisions of Сustoms and Tax legislation on small hydropower regarding to incentives for technology development have been defined. Consideration of small hydropower projects successfully implemented on the territory of the country confirms the possibility of the future development of small hydropower.