• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.11
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• pp.2147-2151
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• 2011

In this paper, we propose the formation control algorithm for swarm robots. The proposed algorithm uses the artificial potential field(APF) to plan the global path of swarm robots and to control the formation movement. The navigation function generates a global APF for a leader robot to reach a given destination and an avoidance function generates a local APF for follow robots to avoid obstacles. Finally, some simulations show the validity of the proposed method.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.403-404
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• 2007

Compound eyes in nature present intriguing topics in physiological optics due to their unique optical scheme for imaging. For example, a bee's eye has thousands of integrated photonic units called ommatidia spherically arranged along a curvilinear surface so that each unit points in a different direction. The omni-directionally arranged ommatidium collects incident light with a narrow range of angular acceptance and independently contributes to the capability of wide field-of-view (FOV) detection. Artificial implementation of compound eyes has attracted a great deal of research interest because the wide FOV exhibits a huge potential for medical, industrial, and military applications. So far, imaging with a FOV over $90^{\circ}$ has been achieved only with fisheye lenses which rely on bulky and expensive multiple lenses and require stringent alignment. In this talk, we will discuss about the spherical 3D arrangement of the photonic structures of biologically inspired artificial compound eyes in a small form-factor to have and the functional and anatomical similiarity with natural compound eyes.

• Smart Structures and Systems
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• v.7 no.3
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• pp.185-198
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• 2011

The promise of biomimetic smart structures that can function as sensors and actuators in biomedicine is enormous. Technological development in the field of stimuli-responsive shape memory polymers have opened up a new avenue of applications for polymer-based synthetic actuators. Such synthetic actuators mimic various attributes of living organisms including responsiveness to stimuli, shape memory, selectivity, motility, and organization. This article briefly reviews various stimuli-responsive shape memory polymers and their application as bioactuators. Although the technological advancements have prototyped the potential applications of these smart materials, their widespread commercialization depends on many factors such as sensitivity, versatility, moldability, robustness, and cost.

• Cartoon and Animation Studies
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• s.50
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• pp.423-452
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• 2018

The possibility of future industrialization of artificial intelligence was studied through aspects of artificial intelligence art and movie. The field of artificial intelligence is developing by imitating humans through past and present, so it can be inferred that it is important to grasp the future image presented in movie and artificial intelligence art. Human values are represented differently in artificial intelligence films and arts. Artificial intelligence film and art are concerned with the external and internal aspects of human values, respectively. The AI movie looks at similar external aspects in human and AI shape and function, but artificial intelligence art deals with human alienation and lack of communication due to artificial intelligence technology development. Artificial intelligence in movies is a direction to visualize the imagination for artificial intelligence technology, and artificial intelligence art is expressed in the way of making and implementing works using technology. The future of artificial intelligence, which we have shown in imagination in movies today, is being realized technologically. Artificial intelligence art reflects the problems of artificial intelligence technology that can be appeared through current technology, and human problems that may arise from artificial intelligence technology development. Movies and artificial intelligence art reflect the current problems, and through them we can see the future of artificial intelligence. The future of artificial intelligence in movies is an artificial intelligence service that provides human convenience, cyborg artificial intelligence industry, industry that uses exoskeleton robot and exoskeleton suit, and artificial intelligence secretary. If we look at the future of artificial intelligence through the artificial intelligence art in terms of the problems of artificial intelligence technology and the problem of human value, there are artificial intelligence to learn from trial and error or mistakes, self-expression and communication by lifelogging, recovery of miscommunications by a reflective thinking, and an expansion of the area of artificial intelligence artist through human uncertainty. The future industrialization potential of artificial intelligence as study through aspects of artificial intelligence art and movie is an industry that extends the five senses, an industry that improves the insufficient physical ability of the human, an industry that enhances the physical ability of the human being, and an industry that maintains psychological and mental well-being.

• Journal of the Korean Chemical Society
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• v.67 no.2
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• pp.89-98
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• 2023

The cell membrane, also known as the biological membrane, surrounds every living cell. The main components of cell membranes are lipids and therefore called as lipid membranes. These membranes are mainly made up of a two-dimensional lipid bilayer along with integral and peripheral proteins. The complex nature of lipid membranes makes it difficult to study and hence artificial lipid membranes are prepared which mimic the original lipid membranes. These artificial lipid membranes are prepared from phospholipid vesicles (liposomes). The liposomes are formed when self-forming phospholipid bilayer comes in contact with water. Liposomes can be unilamellar or multilamellar vesicles which comprises of phospholipids that can be produced naturally or synthetically. The phospholipids are non-toxic, biodegradable and are readily produced on a large scale. These liposomes are mostly used in the drug delivery systems. This paper offers comprehensive literature with insights on developing basic understanding of lipid membranes from its structure, organization, and phase behavior to its potential use in biomedical applications. The progress in the field of artificial membrane models considering methods of preparation of liposomes for mimicking lipid membranes, interactions between the lipid membranes, and characterizing techniques such as UV-visible, FTIR, Calorimetry and X-ray diffraction are explained in a concise manner.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.346-351
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• 2023

With the rapid development of Artificial Intelligence (AI) technology, there is an increasing variety of methods for creating 3D models. These include innovations such as text-only generation, 2D images to 3D models, and combining images with cue words. Each of these methods has unique advantages, opening up new possibilities in the field of 3D modeling. The purpose of this study is to explore and summarize these methods in-depth, providing researchers and practitioners with a comprehensive perspective to understand the potential value of these methods in practical applications. Through a comprehensive analysis of pure text generation, 2D images to 3D models, and images with cue words, we will reveal the advantages and disadvantages of the various methods, as well as their applicability in different scenarios. Ultimately, this study aims to provide a useful reference for the future direction of AI modeling and to promote the innovation and progress of 3D model generation technology.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.127-130
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• 2000

Classification of Electroencephalogram(EEG) makes one of key roles in the field of clinical diagnosis, such as detection for epilepsy. Spectrum analysis using the fourier transform(FT) uses the same window to signals, so classification rate decreases for nonstationary signals such as EEG's. In this paper, wavelet power spectrum method using wavelet transform which is excellent in detection of transient components of time-varying signals is applied to the classification of three types of Event Related Potential(EP) and compared with the result by fourier transform. In the experiments, two types of photic stimulation, which are caused by eye opening/closing and artificial light, are used to collect the data to be classified. After choosing a specific range of scales, scale-averaged wavelet spectrums extracted from the wavelet power spectrum is used to find features by Back-Propagation(13P) algorithm. As a result, wavelet analysis shows superiority to fourier transform for nonstationary EEG signal classification.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.307-313
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• 2024

This study explores the integration of Explainable Artificial Intelligence (XAI) and network science in healthcare, focusing on enhancing healthcare data interpretation and improving diagnostic and treatment methods. Key methodologies like Graph Neural Networks, Community Detection, Overlapping Network Models, and Time-Series Network Analysis are examined in depth for their potential in patient health management. The research highlights the transformative role of XAI in making complex AI models transparent and interpretable, essential for accurate, data-driven decision-making in healthcare. Case studies demonstrate the practical application of these methodologies in predicting diseases, understanding drug interactions, and tracking patient health over time. The study concludes with the immense promise of these advancements in healthcare, despite existing challenges, and underscores the need for ongoing research to fully realize the potential of AI in this field.

• Journal of Korean Neurosurgical Society
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• v.66 no.6
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• pp.632-641
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• 2023

Central nervous system tumors are identified as tumors of the brain and spinal cord. The associated morbidity and mortality of cerebrospinal tumors are disproportionately high compared to other malignancies. While minimally invasive techniques have initiated a revolution in neurosurgery, artificial intelligence (AI) is expediting it. Our study aims to analyze AI's role in the neurosurgical management of cerebrospinal tumors. We conducted a scoping review using the Arksey and O'Malley framework. Upon screening, data extraction and analysis were focused on exploring all potential implications of AI, classification of these implications in the management of cerebrospinal tumors. AI has enhanced the precision of diagnosis of these tumors, enables surgeons to excise the tumor margins completely, thereby reducing the risk of recurrence, and helps to make a more accurate prediction of the patient's prognosis than the conventional methods. AI also offers real-time training to neurosurgeons using virtual and 3D simulation, thereby increasing their confidence and skills during procedures. In addition, robotics is integrated into neurosurgery and identified to increase patient outcomes by making surgery less invasive. AI, including machine learning, is rigorously considered for its applications in the neurosurgical management of cerebrospinal tumors. This field requires further research focused on areas clinically essential in improving the outcome that is also economically feasible for clinical use. The authors suggest that data analysts and neurosurgeons collaborate to explore the full potential of AI.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.37-45
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• 2023

Adaptive has gained significant attention in Education Technology (EdTech), with personalized learning experiences becoming increasingly important. Next-generation chatbots, including models like ChatGPT, are emerging in the field of education. These advanced tools show great potential for delivering personalized and adaptive learning experiences. This paper reviews previous research on adaptive learning and the role of chatbots in education. Based on this, the paper explores current and future chatbot technologies to propose a framework for using ChatGPT or similar chatbots in adaptive learning. The framework includes personalized design, targeted resources and feedback, multi-turn dialogue models, reinforcement learning, and fine-tuning. The proposed framework also considers learning attributes such as age, gender, cognitive ability, prior knowledge, pacing, level of questions, interaction strategies, and learner control. However, the proposed framework has yet to be evaluated for its usability or effectiveness in practice, and the applicability of the framework may vary depending on the specific field of study. Through proposing this framework, we hope to encourage learners to more actively leverage current technologies, and likewise, inspire educators to integrate these technologies more proactively into their curricula. Future research should evaluate the proposed framework through actual implementation and explore how it can be adapted to different domains of study to provide a more comprehensive understanding of its potential applications in adaptive learning.