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Machine-learned wearable sensors for real-time hand-motion recognition: toward practical applications

National Science Review 2024年第2期11卷 231-263页

作者： kyung Rok Pyun Kangkyu Kwon Myung Jin Yoo kyun kyu kim Dohyeon Gong Woon-Hong Yeo Seungyong Han Seung Hwan Ko Department of Mechanical Engineering Seoul National University IEN Center for Human-Centric Interfaces and Engineering Institute for Electronics and NanotechnologyGeorgia Institute of Technology School of Electrical and Computer Engineering Georgia Institute of Technology Department of Chemical Engineering Stanford University Department of Mechanical Engineering Ajou University George W.Woodruff School of Mechanical Engineering Georgia Institute of Technology Institute of Advanced Machinery and Design(SNU-IAMD) Seoul National University

Soft electromechanical sensors have led to a new paradigm of electronic devices for novel motion-based wearable applications in our daily lives. However, the vast amount of random and unidentified signals generated by complex body motions has hindered the precise recognition and practical application of this technology. Recent advancements in artificial-intelligence technology have enabled significant strides in extracting features from massive and intricate data sets, thereby presenting a breakthrough in utilizing wearable sensors for practical applications. Beyond traditional machine-learning techniques for classifying simple gestures, advanced machine-learning algorithms have been developed to handle more complex and nuanced motion-based tasks with restricted training data sets. Machine-learning techniques have improved the ability to perceive, and thus machine-learned wearable soft sensors have enabled accurate and rapid human-gesture recognition, providing real-time feedback to users. This forms a crucial component of future wearable electronics, contributing to a robust human–machine interface. In this review, we provide a comprehensive summary covering materials, structures and machine-learning algorithms for hand-gesture recognition and possible practical applications through machine-learned wearable electromechanical sensors.

关键词： wearable sensor soft electronics artificial intelligence machine learning human–machine interfaces gesture recognition

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2.47 GPa grade ultra-strong 15Co-12Ni secondary hardening steel with superior ductility and fracture toughness

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Journal of Materials Science & Technology 2021年第7期66卷 36-45页

作者： Young-kyun kim kyu-Sik kim Young-Beum Song Jung Hyo Park Kee-Ahn Lee Department of Materials Science and Engineering Inha UniversityIncheon22212Republic of Korea Agency for Defense Development(ADD) Yuseong-guDaegeon34186Republic of Korea

This study investigated the effect of multi-step heat treatment on the microstructure, mechanical properties and fracture behavior of thick 15 Co-12 Ni secondary hardening steel. As-quenched sample was found to have elongated prior austenite grain(PAG) and coarse lenticular martensitic structure. On the other hand, heat-treated sample was observed to have fine lenticular martensitic structure due to fine PAG size and a lot of nano-sized carbides. Also, after heat treatment, nano-scale reverted austenite film was formed at the martensite interfaces. The heat-treated sample showed 2.47 GPa superior tensile strength and superior elongation of about 12 %. The high strength was mainly due to fine block size and high number density of nano-sized carbides. The average value of plane strain fracture toughness(KIC) was 29.3 MPa m1/2, which indicated a good fracture toughness even with the high tensile strength. The tensile fracture surface was observed to have ductile fracture mode(cup-and-cone) and the formation of about ~1 μm ultra-fine dimples. In addition to this, nano-sized carbides were observed within the *** findings suggested that the nano-sized carbide had a positive effect not only on the strength but also on the ductility of the alloy. The fractured surface after toughness test, also showed ductile fracture mode with a lot of dimples. Based on the above results, correlation among microstructural evolution,deformation and fracture mechanisms along the heat-treatment was also discussed.

关键词： Ultra-high strength High Co-Ni secondary hardening steel Microstructure Tensile properties Fracture toughness Reverted austenite

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Stabilized sub-grain and nano carbides-driven 1.2 GPa grade ultra-strong CrMnFeCoNi high-entropy alloy additively manufactured by laser powder bed fusion

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Journal of Materials Science & Technology 2022年第22期117卷 8-22页

作者： Young-kyun kim Kee-Ahn Lee Department of Materials Science and Engineering Inha UniversityIncheon 22212Republic of Korea Korea Institute of Materials Science(kimS) Changwon 51508Republic of Korea

High-entropy alloys(HEAs)with interstitial atoms that are produced by additive manufacturing have gained intensive interest in the materials science community because of their suitability for constructing high-strength net-shape ***,a strategy to additionally enhance the strength of selective laser melted carbon-containing HEAs was *** as-built carbon-containing HEAs(C_(x)(Cr_(20)Mn_(20)Fe_(20)Co_(20)Ni_(20))_(100-x)(x=0.5 at.%,1.0 at.%,and 1.5 at.%))contain supersaturated carbon,and the extent of supersaturation increases as the carbon content *** subjected to aging treatment at 650°C for 1 h,the microstructure of the three alloys did not change at the grain ***,the microstructure at the sub-grain scale changed markedly,and these changes influenced the tensile properties and deformation *** particular,the tensile strength of aged 1.5C-HEA at 650°C was∼1.2 GPa at room temperature,which is higher than those reported for CrMnFeCoNi ***,the main deformation mechanism changed from deformation twinning to dislocation-mediated slip,resulting in much higher strain hardening capacity after the aging *** work led to the development of an alternative promising method that involves tailoring the microstructure,to enhance the mechanical properties of additively manufactured metallic materials that contain interstitial atoms.

关键词： Selective laser melting High-entropy alloy Carbon contents Aging Microstructure evolution Tensile property Deformation mechanism

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Effect of carrier gas species on the microstructure and compressive deformation behaviors of ultra-strong pure copper manufactured by cold spray additive manufacturing

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Journal of Materials Science & Technology 2022年第2期97卷 264-271页

作者： Young-kyun kim Kee-Ahn Lee Department of Materials Science and Engineering Inha UniversityIncheon 22212Republic of Korea

Cold spray(CS)which has recently become a promising additive manufacturing(AM)technology,was used to fabricate ultra-strong pure *** addition,the effects of carrier gas species on the microstructural characteristics,mechanical properties and deformation mechanisms were systemically *** CSAM copper manufactured with N_(2) carrier gas reveals a heterogeneous bimodal microstructure consisting of ultra-fine grains at the particle interface and relatively coarse grains in inner *** He carrier gas,a homogeneous grain structure consisting of ultra-fine grains in most areas was *** tests showed that N_(2) and He carrier gasses enabled ultra-high yield strengths of 340 and415 MPa,*** values are comparable to severely plastic deformed copper,which has extremely low ductility and shape *** the other hand,both samples showed a strain-softening phenomenon that does not commonly occur at room *** deformation microstructures revealed that dynamic recovery(DRV)and dynamic recrystallization(DRX)phenomena were generated despite being deformed at room *** on the above findings,the overall deformation mechanisms according to the carrier gas species in the CSAM copper manufacturing process were ***,the work hardening and softening behaviors of CSAM Cu are predicted by using a constitutive equation.

关键词： Cold spray additive manufacturing Carrier gas Pure Cu Mechanical properties Deformation behavior

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1.45 GPa ultrastrong cryogenic strength with superior impact toughness in the in-situ nano oxide reinforced CrMnFeCoNi high-entropy alloy matrix nanocomposite manufactured by laser powder bed fusion

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Journal of Materials Science & Technology 2022年第2期97卷 10-19页

作者： Young-kyun kim Min-Chul kim Kee-Ahn Lee Department of Materials Science and Engineering Inha UniversityIncheon 22212Republic of Korea Korea Atomic Energy Research Institute(KAERI) Daejeon 34057Republic of Korea

CrMnFeCoNi high-entropy alloys(HEAs)exhibit an excellent combination of tensile strength and ductility at cryogenic *** study led to the introduction of a new method for the development of high-performance CrMnFeCoNi HEAs at cryogenic temperatures by jointly utilizing additive manufacturing(AM)and the addition of interstitial *** interstitial oxygen present in the powder feedstock was transformed into beneficial nano-sized oxides during AM *** HEA nanocomposite fabricated using laser powder bed fusion(L-PBF)not only contains heterogeneous grains and substructures but also a high number density of nano-sized *** tensile results revealed that the L-PBF HEA nanocomposite has superior yield strengths of 0.77 GPa and 1.15 GPa,and tensile strengths of 0.92 GPa and 1.45 GPa at 298 K and 77 K,*** addition,the Charpy impact energies of the samples tested at 298 K and 77 K were measured as 176.2 J and 103.7 J,*** results indicate that the L-PBF HEA nanocomposite successfully overcomes the well-known strength-toughness *** tensile deformation microstructure contained a relatively large number of deformation twins(DTs)at cryogenic temperature,a possible consequence of the decrease in the stacking fault energy with decreasing *** the other hand,cracks were found to propagate along the grain boundaries at room temperature,whereas a transgranular crack was observed at cryogenic temperature in the specimens fractured as a result of the Charpy impact.

关键词： Laser powder bed fusion High-entropy alloy matrix nanocomposite Nano-oxide:cryogenic Tensile Impact toughness

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Outlier Behavior Detection for Indoor Environment Based on t-SNE Clustering

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Computers, Materials & Continua 2021年第9期68卷 3725-3736页

作者： Shinjin Kang Soo kyun kim School of Games Hongik UniversitySejong30016Korea Department of Computer Engineering Jeju National UniversityJeju63243Korea

In this study,we propose a low-cost system that can detect the space outlier utilization of residents in an indoor *** focus on the users’app usage to analyze unusual behavior,especially in indoor *** is reflected in the behavioral analysis in that the frequency of using smartphones in personal spaces has recently *** system facilitates autonomous data collection from mobile app logs and Google app servers and generates a high-dimensional dataset that can detect outlier *** density-based spatial clustering of applications with noise(DBSCAN)algorithm was applied for effective singular movement *** analyze high-level mobile phone usage,the t-distributed stochastic neighbor embedding(t-SNE)algorithm was *** two clustering algorithms can effectively detect outlier behaviors in terms of movement and app usage in indoor *** experimental results showed that our system enables effective spatial behavioral analysis at a low cost when applied to logs collected in actual living ***,large volumes of data required for outlier detection can be easily *** system can automatically detect the unusual behavior of a user in an indoor *** particular,this study aims to reflect the recent trend of the increasing use of smartphones in indoor spaces to the behavioral analysis.

关键词： Outlier detection trajectory clustering behavior analysis app data smartphone

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Design of Learning Media in Mixed Reality for Lao Education

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Computers, Materials & Continua 2020年第7期64卷 161-180页

作者： Kalaphath Kounlaxay Soo kyun kim Department of Game Engineering Pai Chai UniversityDaejeon35345Korea Department of Computer Engineering Jeju National UniversityJeju63243Korea

To improve and develop education systems,the communication between instructors and learners in a class during the learning process is of utmost *** the presentations of 3D models using mixed reality(MR)technology can be used to avoid misinterpretations of oral and 2D model *** an independent concept and MR applications,MR combines the excellent of each virtual reality(VR)and augmented reality(AR).This work aims to present the descriptions of MR systems,which include its devices,applications,and literature reviews and proposes computer vision tracking using the AR Toolkit Tracking *** focus of this work will be on creating 3D models and implementing in Unity 3D using the Vuforia SDK platform to develop VR and AR applications for architectural presentations.

关键词： Mixed reality virtual reality augmented reality Vuforia head-mounted displays.

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Metabolic syndrome is associated with erosive esophagitis

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World Journal of Gastroenterology 2008年第35期14卷 5442-5447页

作者： Jung Ho Park Dong IL Park Hong Joo kim Yong kyun Cho Chong IL Sohn Woo kyu Jeon Byung Ik kim Department of Medicine Kangbuk Samsung HospitalSungkyunkwan University School of MedicineSeoulSouth Korea

AIM： To clarify whether insulin resistance and metabolic syndrome are risk factors for erosive esophagitis.METHODS： A case-control study was performed using the database of the Kangbuk Samsung Hospital Medical Screening Center.RESULTS： A total of 1679 cases of erosive esophagitis and 3358 randomly selected controls were included. Metabolic syndrome was diagnosed in 21% of the cases and 12% of the controls （P 〈 0.001）. Multiple logistic regressions confirmed the association between erosive esophagitis and metabolic syndrome （Odds ratio, 1.25; 95% CI, 1.04-1.49）. Among the components of metabolic syndrome, increased waist circumference, elevated serum triglyceride levels and hypertension were significant risk factors for erosive esophagitis （all P 〈 0.01）. Furthermore, increased insulin resistance （Odds ratio, 0.91; 95% CI, 0.85-0.98） and fatty liver, as diagnosed by ultrasonography （odds ratio, 1.39; 95% CI, 1.20-1.60）, were also related to erosive esophagitis even afl：er adjustment for a series of confounding factors.CONCLUSION： Metabolic syndrome and increased insulin resistance are associated with an increased risk of developing erosive esophagitis.

关键词： Metabolic syndrome Erosive esophagitis Insulin resistance Fatty liver

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On-screen fingerprint sensor with optically and electrically tailored transparent electrode patterns for use on high-resolution mobile displays

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Microsystems & Nanoengineering 2020年第1期6卷 243-254页

作者： Hyun-Joon kim-Lee Seog Woo Hong Dong kyun kim Jinmyoung kim Hong Suk kim Seok-Whan Chung Eun-Hyoung Cho Hae-Sung kim Byung-kyu Lee Device Research Center Samsung Advanced Institute of Technology130 Samsung-roYeongtong-guSuwon-siGyeonggi-do 443-803Republic of Korea

In this study,a mutual capacitive-type on-screen fingerprint sensor,which can recognize fingerprints on a display screen to provide smartphones with full-screen displays with a minimal bezel area,is ***-screen fingerprint sensors are fabricated using an indium tin oxide transparent conductor with a sheet resistance of~10Ω/*** a transmittance of~94%(~86% with the substrate effect)in the visible wavelength range,and assembled onto a display *** at this high transmittance,the electrodes can degrade the display quality when they are placed on the *** interference between periodic display pixel arrays and sensor patterns can lead to the *** is necessary to find an appropriate sensor pattern that minimizes the Moirepattern,while maintaining the signal *** search for appropriate patterns,a numerical calculation is carried out over wide ranges of pitches and rotation *** range is narrowed for an experimental evaluation,which is used to finally determine the sensor *** the selected sensor pitches are too small to detect capacitance variations,three unit patterns are electrically connected to obtain a unit block generating a larger *** applying the selected sensor pattern and circuit driving by block,fingerprint sensing on a display is demonstrated with a prototype built on a commercial smartphone.

关键词： transparent pattern smart

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Game Outlier Behavior Detection System Based on Dynamic Time Warp Algorithm

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Computer Modeling in Engineering & Sciences 2022年第4期131卷 219-237页

作者： Shinjin Kang Soo kyun kim School of Games Hongik UniversitySejong30016Korea Department of Computer Engineering Jeju National UniversityJeju63243Korea

This paper proposes a methodology for using multi-modal data in gameplay to detect outlier *** proposedmethodology collects,synchronizes,and quantifies time-series data fromwebcams,mouses,and *** expressions are varied on a one-dimensional pleasure axis,and changes in expression in the mouth and eye areas are detected ***,the keyboard and mouse input frequencies are tracked to determine the interaction intensity of ***,we apply a dynamic time warp algorithm to detect outlier *** detected outlier behavior graph patterns were the play patterns that the game designer did not intend or play patterns that differed greatly from those of other *** outlier patterns can provide game designers with feedback on the actual play experiences of users of the *** results can be applied to the game industry as game user experience analysis,enabling a quantitative evaluation of the excitement of a game.

关键词： Facial expression recognition webcam behavior analysis affective computing

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