• Title/Summary/Keyword: AI Solutions

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Development and Validation of AI Image Segmentation Model for CT Image-Based Sarcopenia Diagnosis (CT 영상 기반 근감소증 진단을 위한 AI 영상분할 모델 개발 및 검증)

  • Lee Chung-Sub;Lim Dong-Wook;Noh Si-Hyeong;Kim Tae-Hoon;Ko Yousun;Kim Kyung Won;Jeong Chang-Won
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.3
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    • pp.119-126
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    • 2023
  • Sarcopenia is not well known enough to be classified as a disease in 2021 in Korea, but it is recognized as a social problem in developed countries that have entered an aging society. The diagnosis of sarcopenia follows the international standard guidelines presented by the European Working Group for Sarcopenia in Older People (EWGSOP) and the d Asian Working Group for Sarcopenia (AWGS). Recently, it is recommended to evaluate muscle function by using physical performance evaluation, walking speed measurement, and standing test in addition to absolute muscle mass as a diagnostic method. As a representative method for measuring muscle mass, the body composition analysis method using DEXA has been formally implemented in clinical practice. In addition, various studies for measuring muscle mass using abdominal images of MRI or CT are being actively conducted. In this paper, we develop an AI image segmentation model based on abdominal images of CT with a relatively short imaging time for the diagnosis of sarcopenia and describe the multicenter validation. We developed an artificial intelligence model using U-Net that can automatically segment muscle, subcutaneous fat, and visceral fat by selecting the L3 region from the CT image. Also, to evaluate the performance of the model, internal verification was performed by calculating the intersection over union (IOU) of the partitioned area, and the results of external verification using data from other hospitals are shown. Based on the verification results, we tried to review and supplement the problems and solutions.

Introducing SEABOT: Methodological Quests in Southeast Asian Studies

  • Keck, Stephen
    • SUVANNABHUMI
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    • v.10 no.2
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    • pp.181-213
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    • 2018
  • How to study Southeast Asia (SEA)? The need to explore and identify methodologies for studying SEA are inherent in its multifaceted subject matter. At a minimum, the region's rich cultural diversity inhibits both the articulation of decisive defining characteristics and the training of scholars who can write with confidence beyond their specialisms. Consequently, the challenges of understanding the region remain and a consensus regarding the most effective approaches to studying its history, identity and future seem quite unlikely. Furthermore, "Area Studies" more generally, has proved to be a less attractive frame of reference for burgeoning scholarly trends. This paper will propose a new tool to help address these challenges. Even though the science of artificial intelligence (AI) is in its infancy, it has already yielded new approaches to many commercial, scientific and humanistic questions. At this point, AI has been used to produce news, generate better smart phones, deliver more entertainment choices, analyze earthquakes and write fiction. The time has come to explore the possibility that AI can be put at the service of the study of SEA. The paper intends to lay out what would be required to develop SEABOT. This instrument might exist as a robot on the web which might be called upon to make the study of SEA both broader and more comprehensive. The discussion will explore the financial resources, ownership and timeline needed to make SEABOT go from an idea to a reality. SEABOT would draw upon artificial neural networks (ANNs) to mine the region's "Big Data", while synthesizing the information to form new and useful perspectives on SEA. Overcoming significant language issues, applying multidisciplinary methods and drawing upon new yields of information should produce new questions and ways to conceptualize SEA. SEABOT could lead to findings which might not otherwise be achieved. SEABOT's work might well produce outcomes which could open up solutions to immediate regional problems, provide ASEAN planners with new resources and make it possible to eventually define and capitalize on SEA's "soft power". That is, new findings should provide the basis for ASEAN diplomats and policy-makers to develop new modalities of cultural diplomacy and improved governance. Last, SEABOT might also open up avenues to tell the SEA story in new distinctive ways. SEABOT is seen as a heuristic device to explore the results which this instrument might yield. More important the discussion will also raise the possibility that an AI-driven perspective on SEA may prove to be even more problematic than it is beneficial.

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A Study on the Forging of Cylindrical Parts with Internal Serrations (내부에 세레이션홈이 존재하는 원통형 제품의 단조에 관한 연구)

  • Park, J.C.;Cho, H.Y.;Min, G.S.
    • Journal of the Korean Society for Precision Engineering
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    • v.14 no.6
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    • pp.142-148
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    • 1997
  • In this paper, forging of internal triangular and involute serrations are analyzed by upper bound method. Kinematically admissible velocity fields for half pitch of the serration were proposed. It was assumed that the shape flow surface during forging is a straight line perpendicular to plane of symmetry. Using the suggested velocity fields, forging loads and relative pressures were calculated by numerical method. Experiments were carride out with commercial AI 2024 aluminium alloy. As a result, the calculated solutions are good agreement with experimental results, so it is useful to predict the loads for forging of internal serrations.

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GENERALIZED BI-QUASI-VARIATIONAL-LIKE INEQUALITIES ON NON-COMPACT SETS

  • Cho, Yeol Je;Chowdhury, Mohammad S.R.;Ha, Je Ai
    • Communications of the Korean Mathematical Society
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    • v.32 no.4
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    • pp.933-957
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    • 2017
  • In this paper, we prove some existence results of solutions for a new class of generalized bi-quasi-variational-like inequalities (GBQVLI) for (${\eta}-h$)-quasi-pseudo-monotone type I and strongly (${\eta}-h$)-quasi-pseudo-monotone type I operators defined on non-compact sets in locally convex Hausdorff topological vector spaces. To obtain our results on GBQVLI for (${\eta}-h$)-quasi-pseudo-monotone type I and strongly (${\eta}-h$)-quasi-pseudo-monotone type I operators, we use Chowdhury and Tan's generalized version of Ky Fan's minimax inequality as the main tool.

How to Reduce Fire Fatalities in Residential Occupancies on the Way to a Rapidly Aging Society?

  • Sekizawa, Ai
    • Proceedings of the Korea Institute of Fire Science and Engineering Conference
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    • 2006.04a
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    • pp.29-40
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    • 2006
  • Everybody may be vulnerable to fires depending on the time, place, and circumstances. Fire statistics show that the occurrence of fire death depends not only on the severity of a fire itself, but also largely on the conditions of occupants such as physical functions, the environment around occupants, and the type of facility where are fire occurs. The review of fire safety from the viewpoint of vulnerable populations does not simply mean additional special attention and care only to high risk groups, but instead it means significant review of fire safety design and systems for all people from a more universal standpoint. Therefore, in order to examine the strategies of a fire death-reduction program, safety measures suitable for the relevant high-risk groups considering the type of vulnerable person, the type of fire, and the type of building in residential occupancies. Solutions will require strenuous multilateral effort and flexibility.

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Improvement Plan for the Prevention and Biosecurity of Animal Disease (가축전염병 예방 및 방역을 위한 개선방안)

  • Park, Jae Hong
    • Journal of Korean Society on Water Environment
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    • v.27 no.3
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    • pp.371-376
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    • 2011
  • If animal disease, i.e., livestock foot-and-mouth disease, avian influenza, brings out, animals have to be disposed to prevent the virus spreading. Mainly, animals have been disposed by carcass disposal. However, If not done properly, carcass disposal can lead to environmental problems, i.e., soil and ground water pollution, etc. Therefore, various disposal methods, i.e., rendering, cremation, etc., have to be considered with burial. Also, various supplement policies are needed to prevent the animal disease. The purpose of this study was to find effective solutions for the prevention and biosecurity of animal disease.

Standardization Trends for Operation of Unmanned Aerial Vehicles based on 5G (5G 기반 무인 비행체 운용 표준화 동향)

  • Lee, H.;Bae, J.S.;Bahng, S.J.;Lee, H.S.
    • Electronics and Telecommunications Trends
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    • v.36 no.4
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    • pp.13-22
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    • 2021
  • Among the activities of 3GPP for operating 5G-based unmanned aerial vehicles, we introduce several use cases of UAVs in 5G mobile communication such as radio access node onboard UAV, simultaneous support data transmission for UAVs and eMBB users, autonomous UAVs controlled by AI, isolated deployment of radio access through UAV, and separation of UAV service area. From this, we further summarize 5G mobile communication requirements for UAVs, including definition and operational criteria of UAS, UAS remote identification requirements, UAS usage requirements, and performance requirements. Finally, regarding 5G mobile communication-based UAS connectivity, identification and tracking support, we discuss the 3GPP UAV architecture, seven major problems, the proposed solutions to each problem, and propose the results for future specification work.

Using artificial intelligence to solve a smart structure problem

  • Kaiwen, Liu;Jun, Gao;Ruizhe, Qiu
    • Structural Engineering and Mechanics
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    • v.85 no.3
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    • pp.393-406
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    • 2023
  • Smart structures are those structure that could adopt some behavior to prevent instability in their responses. The recognition of stability deterioration has been performed through rigid mathematical formulations in control theory and unpredicted results could not be addressed in control systems since they are able to only work under their predefined condition. On the other hand, incorporating all affecting parameters could result in high computational cost and delay time in the response of the systems. Artificial intelligence (AI) method has shown to be a promising methodology not only in the computer science by at everyday life and in engineering problems. In the present study, we exploit the capabilities of artificial intelligence method to obtain frequency response of a smart structure. In this regard, a comprehensive development of equations is presented using Hamilton' principle and first order shear deformation theory. The equations were solved by numerical methods and the results are used to train an artificial neural network (ANN). It is demonstrated that ANN modeling could provide accurate results in comparison to the numerical solutions and it take less time than numerical solution.

A Review of Structural Testing Methods for ASIC based AI Accelerators

  • Umair, Saeed;Irfan Ali, Tunio;Majid, Hussain;Fayaz Ahmed, Memon;Ayaz Ahmed, Hoshu;Ghulam, Hussain
    • International Journal of Computer Science & Network Security
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    • v.23 no.1
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    • pp.103-111
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    • 2023
  • Implementing conventional DFT solution for arrays of DNN accelerators having large number of processing elements (PEs), without considering architectural characteristics of PEs may incur overwhelming test overheads. Recent DFT based techniques have utilized the homogeneity and dataflow of arrays at PE-level and Core-level for obtaining reduction in; test pattern volume, test time, test power and ATPG runtime. This paper reviews these contemporary test solutions for ASIC based DNN accelerators. Mainly, the proposed test architectures, pattern application method with their objectives are reviewed. It is observed that exploitation of architectural characteristic such as homogeneity and dataflow of PEs/ arrays results in reduced test overheads.

Simulating the performance of the reinforced concrete beam using artificial intelligence

  • Yong Cao;Ruizhe Qiu;Wei Qi
    • Advances in concrete construction
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    • v.15 no.4
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    • pp.269-286
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    • 2023
  • In the present study, we aim to utilize the numerical solution frequency results of functionally graded beam under thermal and dynamic loadings to train and test an artificial neural network. In this regard, shear deformable functionally-graded beam structure is considered for obtaining the natural frequency in different conditions of boundary and material grading indices. In this regard, both analytical and numerical solutions based on Navier's approach and differential quadrature method are presented to obtain effects of different parameters on the natural frequency of the structure. Further, the numerical results are utilized to train an artificial neural network (ANN) using AdaGrad optimization algorithm. Finally, the results of the ANN and other solution procedure are presented and comprehensive parametric study is presented to observe effects of geometrical, material and boundary conditions of the free oscillation frequency of the functionally graded beam structure.