• Korean Journal of Materials Research
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• v.33 no.5
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• pp.175-188
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• 2023

Water electrolysis holds great potential as a method for producing renewable hydrogen fuel at large-scale, and to replace the fossil fuels responsible for greenhouse gases emissions and global climate change. To reduce the cost of hydrogen and make it competitive against fossil fuels, the efficiency of green hydrogen production should be maximized. This requires superior electrocatalysts to reduce the reaction energy barriers. The development of catalytic materials has mostly relied on empirical, trial-and-error methods because of the complicated, multidimensional, and dynamic nature of catalysis, requiring significant time and effort to find optimized multicomponent catalysts under a variety of reaction conditions. The ultimate goal for all researchers in the materials science and engineering field is the rational and efficient design of materials with desired performance. Discovering and understanding new catalysts with desired properties is at the heart of materials science research. This process can benefit from machine learning (ML), given the complex nature of catalytic reactions and vast range of candidate materials. This review summarizes recent achievements in catalysts discovery for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). The basic concepts of ML algorithms and practical guides for materials scientists are also demonstrated. The challenges and strategies of applying ML are discussed, which should be collaboratively addressed by materials scientists and ML communities. The ultimate integration of ML in catalyst development is expected to accelerate the design, discovery, optimization, and interpretation of superior electrocatalysts, to realize a carbon-free ecosystem based on green hydrogen.

• The Journal of the Acoustical Society of Korea
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• v.25 no.2
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• pp.61-71
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• 2006

An MP3 encoder chip has been designed and fabricated with the hardware and software co-design concepts. In the aspect of the software. the calculation cycles of the distortion control loop. which requires most of the calculation cycles in MP3 encoding procedure. have been reduced to $67\%$ of the original algorithm through the 'scale factor Pre-calculation'. By using a floating Point 32 bit DSP core and designing the FFT block with the hardware. we can get the additional reduction of the calculation cycles in addition to the software optimization. The designed chip has been verified using HW emulation and fabricated via 0.25um CMOS technology The fabricated chip has the size of $6.2{\time}6.2mm^2$ and operates normally on the test board in the qualitative and quantitative aspect.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.171.2-171.2
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• 2016

The 2-dimensiona electron gas (2DEG) layers have opened tremendous interests in the heterooxide interfaces formed between two insulating materials, especially between LaAlO3 and $SrTiO_3$. The 2DEG layers exhibit extremely high mobility and carrier concentrations along with metallic transport phenomena unlike the constituent oxide materials, i.e., $LaAlO_3$ and $SrTiO_3$. The current work inserted artificially the interfacial layer, $Sr_xCa_{1-x}TiO_3$ between $LaAlO_3$ and $SrTiO_3$, with the aim to controlling the 2-dimensional transports. The insertion of the additional materials affect significantly their corresponding electrical transports. Such features have been probed using DC and AC-based characterizations. In particular, impedance spectroscopy was employed as an AC-based characterization tool. Frequency-dependent impedance spectroscopy have been widely applied to a number of electroceramic materials, such as varistors, MLCCs, solid electrolytes, etc. Impedance spectroscopy provides powerful information on the materials system: i) the simultaneous measurement of conductivity and dielectric constants, ii) systematic identification of electrical origins among bulk-, grain boundary-, and electrode-based responses, and iii) the numerical estimation on the uniformity of the electrical origins. Impedance spectroscopy was applied to the $LaAlO_3/Sr_xCa_{1-x}TiO_3/SrTiO_3$ system, in order to understand the 2-dimensional transports in terms of the interfacial design concepts. The 2-dimensional conduction behavior system is analyzed with special emphasis on the underlying mechanisms. Such approach is discussed towards rational optimization of the 2-dimensional nanoelectronic devices.

• Journal of Service Research and Studies
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• v.3 no.2
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• pp.75-89
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• 2013

In the services industry and firms, the successful new service development is very important issue today, But the innovation process for service firms is comprehensively little treated until now. This study was performed to suggest the new service development process model for the firms level in the perspective of the radical service innovation. So, in this paper the new process development model can be made by reviewing the concepts about the radical service innovation and by analyzing the some existing new service development process models. In the suggested service development process model, the three key process such as technology forecast, market analysis, and strategy development were included for front phase activity as the new service development process. Also the four key process for searching phase, and the other three key process for implementation phase were included. And for the application for the service firms' service innovation, the innovation's outcome estimation reference model is included. I hope to be executed the various case research and the improvement and optimization for this suggested process model in the future.

• Communications of Mathematical Education
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• v.34 no.1
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• pp.1-15
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• 2020

Today's healthcare, intelligent robots, smart home systems, and car sharing are already innovating with cutting-edge information and communication technologies such as Artificial Intelligence (AI), the Internet of Things, the Internet of Intelligent Things, and Big data. It is deeply affecting our lives. In the factory, robots have been working for humans more than several decades (FA, OA), AI doctors are also working in hospitals (Dr. Watson), AI speakers (Giga Genie) and AI assistants (Siri, Bixby, Google Assistant) are working to improve Natural Language Process. Now, in order to understand AI, knowledge of mathematics becomes essential, not a choice. Thus, mathematicians have been given a role in explaining such mathematics that make these things possible behind AI. Therefore, the authors wrote a textbook 'Basic Mathematics for Artificial Intelligence' by arranging the mathematics concepts and tools needed to understand AI and machine learning in one or two semesters, and organized lectures for undergraduate and graduate students of various majors to explore careers in artificial intelligence. In this paper, we share our experience of conducting this class with the full contents in http://matrix.skku.ac.kr/math4ai/.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.10
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• pp.791-799
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• 2020

Launched in October 2019, Northrop Grumman's MEV-1 was the world's first unmanned mission demonstrating the practical feasibility of on-orbit servicing. Although the concept of on-orbit servicing was proposed several decades ago, it has been developed to various mission concepts providing services such as orbit change, station keeping, propellant and equipment supply, upgrade, repair, on-orbit assembly and production, and space debris removal. The historical success of MEV-1 is expected to expand the market of on-orbit servicing for government agencies and commercial sectors worldwide. The on-orbit servicing essentially requires the utilization of a highly propellant efficient electric propulsion system due to the nature of the mission. In this study, the space mission analysis for a simple on-orbit mission involving Hall thruster is conducted, which is life extension mission for geostationary orbit satellites. In order to analyze the mission, design space exploration for various Hall thruster design variable combinations is performed. The values of design variables and operational parameters of Hall thruster suitable for the mission are proposed through design space analysis and optimization, and mission performance is derived. In addition, the direction of further improvement for the current on-orbit mission analysis process and space mission analysis involving Hall thruster is reviewed.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.251-275
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• 2011

In this paper, we propose a novel kernel called a semantic parse tree kernel that extends the parse tree kernel previously studied to extract protein-protein interactions(PPIs) and shown prominent results. Among the drawbacks of the existing parse tree kernel is that it could degenerate the overall performance of PPI extraction because the kernel function may produce lower kernel values of two sentences than the actual analogy between them due to the simple comparison mechanisms handling only the superficial aspects of the constituting words. The new kernel can compute the lexical semantic similarity as well as the syntactic analogy between two parse trees of target sentences. In order to calculate the lexical semantic similarity, it incorporates context-based word sense disambiguation producing synsets in WordNet as its outputs, which, in turn, can be transformed into more general ones. In experiments, we introduced two new parameters: tree kernel decay factors, and degrees of abstracting lexical concepts which can accelerate the optimization of PPI extraction performance in addition to the conventional SVM's regularization factor. Through these multi-strategic experiments, we confirmed the pivotal role of the newly applied parameters. Additionally, the experimental results showed that semantic parse tree kernel is superior to the conventional kernels especially in the PPI classification tasks.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.307-319
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• 2023

This study aims to explain the key concepts and principles of text-based generative artificial intelligence (AI) that has been receiving increasing interest and utilization, focusing on its application in science education. It also highlights the potential and limitations of utilizing generative AI in science education, providing insights for its implementation and research aspects. Recent advancements in generative AI, predominantly based on transformer models consisting of encoders and decoders, have shown remarkable progress through optimization of reinforcement learning and reward models using human feedback, as well as understanding context. Particularly, it can perform various functions such as writing, summarizing, keyword extraction, evaluation, and feedback based on the ability to understand various user questions and intents. It also offers practical utility in diagnosing learners and structuring educational content based on provided examples by educators. However, it is necessary to examine the concerns regarding the limitations of generative AI, including the potential for conveying inaccurate facts or knowledge, bias resulting from overconfidence, and uncertainties regarding its impact on user attitudes or emotions. Moreover, the responses provided by generative AI are probabilistic based on response data from many individuals, which raises concerns about limiting insightful and innovative thinking that may offer different perspectives or ideas. In light of these considerations, this study provides practical suggestions for the positive utilization of AI in science education.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.