• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.136-141
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• 2023

Artificial intelligence is becoming a global hot topic and is being actively applied in various industrial fields. Not only is artificial intelligence being applied to industrial sites in an on-premises method, but cloud-based artificial intelligence platforms are expanding into "as a service" type. The purpose of this study is to develop and verify a measurement tool for an evaluation framework for the adoption of a cloud-based artificial intelligence platform and test the interrelationships of evaluation variables. To achieve this purpose, empirical testing was conducted to verify the hypothesis using an expanded technology acceptance model, and factors affecting the intention to adopt a cloud-based artificial intelligence platform were analyzed. The results of this study are intended to increase user awareness of cloud-based artificial intelligence platforms and help various industries adopt them through the evaluation framework.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1512-1523
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• 2022

Artificial intelligence application in digital health care has been increasing with its development of artificial intelligence. The convergence of the healthcare industry and information and communication technology makes the diagnosis of diseases more simple and comprehensible. From the perspective of medical services, its practice as an initial test and a reference indicator may become widely applicable. Therefore, analyzing the factors that are the basis for existing diagnosis protocols also helps suggest directions using artificial intelligence beyond previous regression and statistical analyses. This paper conducts essential diagnostic prediction learning based on the analysis of blood cancer factors reported previously. Blood cancer diagnosis predictions based on artificial intelligence contribute to successfully achieve more than 90% accuracy and validation of blood cancer factors as an alternative auxiliary approach.

• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.133-137
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• 2022

In the smart industry where data plays an important role, cloud computing is being used in a complex and advanced way as a convergence technology because it has and fits well with its strengths. Accordingly, in order to utilize artificial intelligence rather than human beings for quality management of cloud computing services, a consistent standardization method of data collected from various nodes in various areas is required. Therefore, this study analyzed technologies and cases for incorporating artificial intelligence into specific services through previous studies, suggested a plan to use artificial intelligence to comprehensively standardize data in quality management of cloud computing services, and then verified it through case studies. It can also be applied to the artificial intelligence learning model that analyzes the risks arising from the data formalization method presented in this study and predicts the quality risks that are likely to occur. However, there is also a limitation that separate policy development for service quality management needs to be supplemented.

• Journal of IKEEE
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• v.27 no.3
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• pp.350-354
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• 2023

This paper describes ISO/IEC TR 24029-1, an international standard to evaluate the performance of artificial intelligence systems. ISO/IEC TR 24029-1 defines the performance measures of artificial intelligence systems in two categories, i.e. interpolation and classificiation. Performance measures in the interpolation categories mean how much the predicted values of the artificial intelligence system is close to the real values. Performance measures in the classification categories mean how much the predicted classes of the artificial intelligence system is equal to the real classes. Based on these performance measures, performance of artificial intelligence systems can be evaluated and performance of different artificial intelligence systems can be compared.

• Electronics and Telecommunications Trends
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• v.39 no.2
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• pp.66-76
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• 2024

Artificial-intelligence (AI) semiconductors are crucial for securing national core competitiveness, including dominating the AI and data ecosystem and succeeding in the Digital New Deal. When examining the macroenvironment, the global division of labor in the semiconductor industry has weakened owing to the technological competition between the United States and China. Major countries are aiming to build the entire semiconductor ecosystem around their territories. As a result, these countries are formulating policy goals tailored to their realities and actively pursuing key policies such as research and development, securing manufacturing bases, workforce development, and financial support. These policies also focus on intercountry cooperation and bold government policy support, which is deemed essential. To secure core competitiveness in AI semiconductors, South Korea needs to examine the policy directions of major countries and actively formulate and implement policies for this semiconductor industry.

• Journal of the Semiconductor & Display Technology
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• v.18 no.3
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• pp.93-99
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• 2019

It is a wine recommendation application service designed for people who sometimes drink wine but lack information and have no place to recommend. This study is to develop UI display design method of wine recommendation service using chatbot. The research method was a case study on Korean wine market, a case study on artificial intelligence market, SWOT analysis of wine-related chatbots, and a competitor analysis of related industries. In addition, surveys and in-depth interviews examined the level of interest and understanding of chatbots, and what kind of chatbots they had encountered and what requirements and goals they faced. After grasping the needs and requirements of users, we created a service concept sheet according to them and produced an application UI design that users can use most easily. Therefore, this study is meaningful in that it proposes a UI design that can search wine information more sophisticated and convenient than face-to-face communication through artificial intelligence service called chatbot and recommend wines that match the taste.

• Journal of the Semiconductor & Display Technology
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• v.18 no.2
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• pp.78-81
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• 2019

In this study, we will analyze the design, development and application of these small drones using open source. These drones are used in flight exercises, aerial photography, and coding education. In the era of the fourth industrial revolution, such as the development of sensor technology, expansion of open source sharing, and application of artificial intelligence, Is expected to be able to demonstrate convergence. In this paper, we have studied the design and fabrication of small drones using open source. In the case of drones, various functions and differentiated materials are required depending on the application, and the future development of the unmanned mobile object, namely the drone, in which the creativity and the technology are combined with each other continues to be enhanced by the improvement of autonomy and artificial intelligence. Software-based architecture-based technologies have been developed in collaboration with embedded SWs that combine sensors, motors, and control systems. In hardware, it is customary to use a combination of materials and design to increase the freedom of design. It will be made in a free structure.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.3
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• pp.11-19
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• 2023

Recently with the rapid advancement of artificial intelligence (AI) technologies such as Chat GPT, AI semiconductors have become important. AI technologies require the ability to process large volumes of data quickly, as they perform tasks such as big data processing, deep learning, and algorithms. However, AI semiconductors encounter challenges with excessive power consumption and data bottlenecks during the processing of large-scale data. Thus, the latest packaging technologies are required for AI semiconductor computations. In this study, the authors have described packaging technologies applicable to AI semiconductors, including interposers, Through-Silicon-Via (TSV), bumping, Chiplet, and hybrid bonding. These technologies are expected to contribute to enhance the power efficiency and processing speed of AI semiconductors.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.104-112
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• 2023

Agriculture plays an industrial and economic role, as well as an environmental and ecological conservation role, group harmony and the inheritance of traditional culture. However, no matter how advanced the industry is, the basic food necessary for human life can only be produced through the photosynthesis of plants with natural resources such as the sun, water, and air. The Food and Agriculture Organization of the United Nations (FAO) predicts that the world's population will increase by another 2 billion people by 2050, and it faces a myriad of complex and diverse factors to consider, including climate change, food security concerns, and global ecosystems and political factors. In particular, in order to solve problems such as increasing productivity and production of agricultural products, improving quality, and saving energy, it is difficult to solve them with traditional farming methods. Recently, with the wind of the 4th industrial revolution, ICT convergence technology and artificial intelligence have been rapidly developing in many fields, but it is also true that the application of new technologies is somewhat delayed due to the unique characteristics of agriculture. However, in recent years, as ICT and artificial intelligence utilization technologies have been developed and applied by many researchers, a revolution is also taking place in agriculture. This paper summarizes the current state of research so far in four categories of agriculture, namely crop cultivation environment management, soil management, pest management, and irrigation management, and smart farm research data that has recently been actively developed around the world.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.6-10
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• 2023

High-potential data can be predicted and stored in the cache to prevent cache misses, thus reducing the processor's request and wait times. As a result, the processor can work non-stop, hiding memory latency. By utilizing the temporal/spatial locality of memory access, the prefetcher introduced to improve the performance of these computers predicts the following memory address will be accessed. We propose a prefetcher that applies the GRU model, which is advantageous for handling time series data. Display the currently accessed address in binary and use it as training data to train the Gated Recurrent Unit model based on the difference (delta) between consecutive memory accesses. Finally, using a GRU model with learned memory access patterns, the proposed data prefetcher predicts the memory address to be accessed next. We have compared the model with the multi-layer perceptron, but our prefetcher showed better results than the Multi-Layer Perceptron.