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Functional Materials Based Surface Acoustic Wave Sensors: A Mini Review
Get PDFSurface acoustic wave (SAW) sensors are widely recognized for their high sensitivity and reliability, which make them suitable for diverse applications. However, they continue to face limitations in repeatability, detection limits, and effective use in extreme environments as well as in biosensing and industrial settings. A critical factor in enhancing the performance of SAW sensors lies not only in the selection of advanced sensing materials but also in the precise methods of material integration. Recent advancements have com-bined nanostructured materials, which improve the surface characteristics, with analyte-specific substances that strengthen interactions, resulting in heightened sensitivity and accuracy. This review categorizes recent SAW sensor studies based on their applications and materials and provides an extensive overview for researchers. Additionally, it highlights how integration techniques affect the uniformity, thickness, and stability of the sensing films, all of which are essential for high-performance sensors. This study aimed to serve as a valu-able resource for the development of SAW sensors with high reliability and longevity under challenging conditions. © 2024, Korean Sensors Society. All rights reserved.TRUEscopuskc
메트릭 학습을 통해 향상된 단안 3D 객체 감지
No full textMonocular 3D object detection, Autonomous driving, Recognition, Regression, Metric LearningMonocular 3D object detection poses a significant challenge due to the lack of depth information in RGB images. Many existing methods strive to enhance the object depth estimation performance by allocating additional parameters for object depth estimation, utilizing extra modules or data. In contrast, we introduce a novel metric learning scheme that encourages the model to extract depth-discriminative features regardless of the visual attributes without increasing inference time and model size. Our method employs the distance- preserving function to organize the feature space manifold in relation to ground-truth object depth. The proposed (, , )-quasi-isometric loss leverages predetermined pairwise distance restriction as guidance for adjusting the distance among object descriptors without disrupting the non-linearity of the natural feature manifold. Moreover, we introduce an auxiliary head for object-wise depth estimation, which enhances depth quality while maintaining the inference time. The broad applicability of our method is demonstrated through experiments that show improvements in overall performance when integrated into various baselines. The results show that our method consistently improves the performance of various baselines by 25.27% and 4.54% on average across KITTI and Waymo, respectively.|단안 3D 객체 감지는 RGB 이미지에서의 깊이 정보 부족으로 인해 상당한 어려움을 가지고 있습니다. 많은 기존 방법들은 객체 깊이 추정 성능을 향상시키기 위해 추가 매개변수를 할당하거나 추가 모듈 또는 데이터를 활용하여 시도하고 있습니다. 이와 반대되게 본 논문에서는 시각적 특성을 고려하지 않고도 모델이 깊이가 잘 구별되는 특징을 추출하도록 하는 새로운 메트릭 학습 체계를 제안합니다. 이 방법은 추론 시간과 모델 크기를 늘리지 않으면서 모델이 시각적 특성과 상관없이 향상된 깊이 특징을 추출하도록 하는 거리 보존 함수를 활용하였다. 제안된 (, , ) -준등거리 손실함수는 객체 쌍 거리의 제한 조건을 활용하여 객체마다의 거리를 객체 깊이 라벨을 통해 정렬하며, 국소적으로 작용함으로써 고차원 공간에 존재하는 특징 매니폴드의 비선형성을 깨뜨리지 않습니다. 또한, 객체별 깊이 추정을 위한 보조 헤드를 도입함으로써 추론 시간을 증가시키지 않고 객체 깊이의 품질을 향상시켰습니다. KITTI 및 Waymo 데이터셋에서의 실험 결과는 다양한 기준선에 걸쳐 일관된 성능 향상을 보여주며 제안된 방법들의 효과를 강조합니다. 향후 작업으로, 우리의 방법은 다중 카메라 3D 객체 감지 시나리오 및 여러 하위 작업을 포함하는 다른 회귀 작업으로 확장될 가능성이 있습니다.I. Introduction 1
II. Related Work 2
III. Method 3
3.1 Preliminary 3
3.2 Problem Definition 4
3.3 Methodology 5
IV. Experiments 10
4.1 Evaluation Results on KITTI/Waymo Datasets 12
4.2 Additional Experiments 12
V. Theoretical Analysis 17
5.1 Pseudo-geodesic 17
5.2 Non-linearity Preservation via Local-constraint 19
VI. Conclusion 20
VII. References 21
VIII. 요약문 25MasterdCollectio
Targeting tumour markers in ovarian cancer treatment
No full textOvarian cancers (OC) are the most common, lethal, and stage-dependent cancers at the global level, specifically in female patients. Targeted therapies involve the administration of drugs that specifically target the alterations in tumour cells responsible for their growth, proliferation, and metastasis, with the aim of treating particular patients. Presently, within the realm of gynaecological malignancies, specifically in breast and OCs, there exist various prospective therapeutic targets encompassing tumour-intrinsic signalling pathways, angiogenesis, homologous-recombination deficit, hormone receptors, and immunologic components. Breast cancers are often detected in advanced stages, primarily due to the lack of a reliable screening method. However, various tumour markers have been extensively researched and employed to evaluate the condition, progression, and effectiveness of medication treatments for this ailment. The emergence of recent technological advancements in the domains of bioinformatics, genomics, proteomics, and metabolomics has facilitated the exploration and identification of hitherto unknown biomarkers. The primary objective of this comprehensive review is to meticulously investigate and analyze both established and emerging methodologies employed in the identification of tumour markers associated with OC. © 2024 Elsevier B.V.FALSEsciescopu
Remote Heart Rate Estimation using Swin Transformer V2 and Wrapping Temporal Shift Modules
Get PDFRemote heart rate (rHR) estimation, which aims to measure heart activities without any physical contact with the subject, is performed using remote photoplethys- mography (rPPG) and has great potential in many applications. In this paper, we introduce a remote heart rate (rHR) estimation algorithm using Swin Transformer V2 and Wrapping Temporal Shift Modules (WTSM). Moreover, we apply difference layer to reduce the lighting and motion noise and shallow stem to extract coarse local spatio-temporal features. Finally, we apply linear layer to project features to 1D rPPG signal and estimate heart rate using FFT. To evaluate the performance of the proposed algorithm, we train and test on the public UBFC-rPPG and PURE dataset. The experimental results show that the proposed algorithm achieve better accuracy than CNN based methods.TRUEforeig
Actuation and Sensing System for Epidural Injection
No full textMeasuring and controlling the contact force between tissues and surgical instruments is critical but challenging in robot-assisted and minimally invasive procedures. A representative minimally invasive procedure, epidural injection aims to minimize nerve damage and employs a contact force-based loss of resistance (LOR) technique to position the needle within the epidural space. Applying the principles of the LOR technique, several studies have proposed sensors and needle systems capable of measuring the contact force between biological tissues and epidural needles. However, further research is needed to quantitatively evaluate system performance within the epidural injection procedure and develop a precise robotic system to drive it. This study proposes a sensor and needle injection system for measuring contact force and quantitatively demonstrates its performance according to the epidural injection procedure
Photovoltaic Effect De-Embedded Photonic C-V Characterization of Subgap Density of States in Amorphous Oxide Semiconductor Thin-Film Transistors
No full textThe subgap density of states (E) is a critical parameter governing the electrical characteristics and short-/long-term reliability of amorphous oxide semiconductor thin-film transistors (AOS TFTs). In this study, we propose an advanced technique for g(DOS) (E) in AOS TFTs through the photonic capacitance-voltage (C-V) characterization. We focused on the gate voltage (V-G) dependence of the photovoltaic effect (PVE), which has not been considered in previous studies. The PVE strongly depends on the amount of g(DOS)(E) reacting in each energy interval, requiring the consideration of V-G -dependency. Furthermore, we incorporated the V-G-dependency of the parasitic capacitance into the equivalent capacitance model, resulting in a more accurate extraction of g(DOS) (E). For validation, the proposed method was applied to amorphous indium-gallium-zinc-oxide (a-IGZO) TFTs with an optical source with lambda=532 nm and obtained N-T = 6 x 10(15 )cm(-3)eV(-1),N-D= 7 x 10(13)cm(-3)eV(-1),kT(T )= 0.28 eV, and kT(D )= 0.7 eV of the exponential and gaussian superposed model of g(DOS)(E). The proposed method isexpected to be a useful tool in the characterization of AOSTFTs.FALSEsciescopu
Bioinspired Technique for Antibody Immobilization on Various Surfaces
No full textBiosensors are vital for disease diagnosis and therapeutic monitoring, but many struggle with effectively immobilizing biological probes due to unsuitable chemical interactions. To solve this, we present a one-pot coating method inspired by marine organisms' adhesive mechanisms, utilizing the exceptional properties of polydopamine. Known for its hydrophilicity and versatile affinity for various substrates, polydopamine acts as a robust adhesive polymer, enhancing the attachment of neutravidin to sensor surfaces. This improves antibody immobilization through strong avidin-biotin interactions, leading to a significant increase in detection sensitivity. Validation with model biomarkers showed more than a tenfold improvement in sensitivity compared to commercial immuno-plates. This approach highlights the transformative potential of polydopamine in biosensor technology, offering a straightforward and effective solution to enhance biosensor performance in diverse biological applications
LEO Satellite Hybrid Beamforming with Reconfigurable Intelligent Surface Deployment
No full textThis paper proposes the design of a hybrid beamformer and the optimization of reconfigurable intelligent surface (RIS) location in a satellite networks. To maximize the downlink data rate, we optimize the hybrid beamforming vector for given RIS location and find the optimal RIS location. We demonstrate that the performance of hybrid beamforming is almost comparable to the ideal fully digital beamforming, and we also find the optimal RIS location. © 2024 IEEE
Planar Omnidirectional Magnetoimpedance-Based Sensors With Microspiral Patterns
No full textThe present work introduces a novel magnetoimpedance (MI) planar microsensor. Various spiral-style (N-sided regular concentric polygons with N = 4, 5, 6, and 7) and line-style (single line (SL) and meander (MD) type) sensors were fabricated from 20-mu m-thick amorphous FeSiC ribbons by using laser ablation and wet etching techniques. These designs were later systematically investigated to evaluate their performance characteristics. The spiral-style sensors show an omnidirectional MI response with significant reduction or even elimination of the magnetic anisotropy typically observed in conventional line-style ones. Significantly, the overall relative MI value of the spiral sensors is approximately 120%, which is comparable to 150% observed in conventional MD-type sensors. In addition, the resonant frequencies of spiral sensors dramatically decrease below 1 GHz in comparison to that of 4 GHz in the MD one and are fully explained through the LCR resonance circuits. The magnetic domain structure as well as the transverse component contribution of magnetic moments obtained from simulations provide a comprehensive understanding of isotropic response mechanism. This study paves a new path in designing omnidirectional planar sensor devices for biomedical applications.FALSEsciescopu
SLIP Embodied Robust Quadruped Robot Control
No full textRecent research on quadruped robots has been achieving high-performance motion control based on optimization and reinforcement learning (RL). However, there is still ongoing research aimed at demonstrating that implementing high-performance motion based on simple and dominant dynamic principles is possible. In this paper, we proposed a novel control approach that projects Spring-Loaded Inverted Pendulum (SLIP) dynamics to articulated legs, utilizing admittance control based force observer within a rotating workspace (RWFOB). Unlike other legged robots that depend on sensor-based estimation of external forces, the proposed method presents an alternative approach that reduces the reliance on sensors. Additionally, we introduce a comprehensive control framework for quadruped robot motion control, establishing the connection between trunk and SLIP-realized leg movements using Jacobian. Through comparative analysis with Virtual Model Control (VMC) in simulations, we illustrate the effectiveness of the proposed framework as a robust and reliable trunk feedback controller. © 2024 IEEE