26 research outputs found
Inversion and Tunability of Van Hove Singularities in VSb ( = K, Rb, and Cs) kagome metals
No full textTo understand the alkali-metal-dependent material properties of recently
discovered VSb ( = K, Rb, and Cs), we conducted a detailed
electronic structure analysis based on first-principles density functional
theory calculations. Contrary to the case of = K and Rb, the energetic
positions of the low-lying Van Hove singularities are reversed in
CsVSb, and the characteristic higher-order Van Hove point gets
closer to the Fermi level. We found that this notable difference can be
attributed to the chemical effect, apart from structural differences. Due to
their different orbital compositions, Van Hove points show qualitatively
different responses to the structure changes. A previously unnoticed highest
lying point can be lowered, locating close to or even below the other ones in
response to a reasonable range of bi- and uni-axial strain. Our results can be
useful in better understanding the material-dependent features reported in this
family and in realizing experimental control of exotic quantum phases.Comment: Physical Chemistry Chemical Physics (PCCP) in pres
Zero-bias anomaly and role of electronic correlations in a disordered metal film
No full textLocalization and electron correlation play significant roles in understanding the electronic states of low-dimensional systems. We carried out the tunneling spectroscopy measurements on a crystalline nano-sized island and a disordered two-dimensional metal film. The low temperature zero-bias anomaly was studied using theory and statistical analysis of the spatial distribution of the local density of states in both the systems. The effective capacitance and resistance of the tunnel junction extracted from theory gives the energy and temperature dependency of the measured ZBA. Statistical analysis reveals the electron correlation effect and the electron correlation length. By combining theory and the statistical analysis, we found that the microscopic origin of ZBA formation in the disordered two-dimensional film is strongly related to the electron localization and the correlations. © 2020 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft.1
PolyFit: A Peg-in-hole Assembly Framework for Unseen Polygon Shapes via Sim-to-real Adaptation
No full textThe study addresses the foundational and challenging task of peg-in-hole
assembly in robotics, where misalignments caused by sensor inaccuracies and
mechanical errors often result in insertion failures or jamming. This research
introduces PolyFit, representing a paradigm shift by transitioning from a
reinforcement learning approach to a supervised learning methodology. PolyFit
is a Force/Torque (F/T)-based supervised learning framework designed for 5-DoF
peg-in-hole assembly. It utilizes F/T data for accurate extrinsic pose
estimation and adjusts the peg pose to rectify misalignments. Extensive
training in a simulated environment involves a dataset encompassing a diverse
range of peg-hole shapes, extrinsic poses, and their corresponding contact F/T
readings. To enhance extrinsic pose estimation, a multi-point contact strategy
is integrated into the model input, recognizing that identical F/T readings can
indicate different poses. The study proposes a sim-to-real adaptation method
for real-world application, using a sim-real paired dataset to enable effective
generalization to complex and unseen polygon shapes. PolyFit achieves
impressive peg-in-hole success rates of 97.3% and 96.3% for seen and unseen
shapes in simulations, respectively. Real-world evaluations further demonstrate
substantial success rates of 86.7% and 85.0%, highlighting the robustness and
adaptability of the proposed method.Comment: 8 pages, 8 figures, 3 table
Sandwich immumoassay - a simple strategy for enhancement of the sensitivity and the specificity in prostate specific antigen detection based on surface plasmon resonance
No full textIRIS-A New Plagiarized Code Detection System
No full textPlagiarism is defined as an activity to use someone\u27s work without the author\u27s agreement or without a proper citation about the reference[l]. To detect plagiarized programming source codes should be performed by instructors to promote the quality of school education. However, it is virtually impossible to detect those source codes completely within the limited time by only using human\u27s ability. Therefore, it is natural to try to adopt computing power to this operation. Most of the existing plagiarism detection systems use an algorithm to find Longest Common Subsection to measure the similarity between two program sources, but does not provide a way to compare algorithms used for those program source files[2-6]. In this paper, we discuss how to build a new detection system named IRIS that uses Strict Binary Tree structure that was introduced in JK system[7] and execution function call sequences in order to determine the algorithms used in program source files, which will be the major factor to measure the similarity of two compared files by applying Software Metrics additionally
Microelectromechanical Switch with Carbon Nanotube Arrays for High-Temperature Operation
No full textFlexible tactile sensors based on gold nanoparticles-precipitated carbon nanotubes with low contact resistance and high sensitivity
No full textAbstract Flexible tactile sensors are receiving considerable interest due to their potential in diverse fields, including physiological monitoring and wearable electronics. Despite numerous studies to broaden their practical use, it remains difficult to simultaneously attain high sensitivity and a wide-range pressure detection. In this study, we have fabricated a tactile sensor with highly porous three-dimensional conductive architecture based on carbon nanotubes (CNTs) functionalized with gold nanoparticles (AuNPs). The zero-dimensional AuNPs, directly precipitated onto the CNT surface, exerted minimal effect on the sensor’s initial resistance. Upon applying pressure to the tactile sensor, the contact resistance among the AuNPs-precipitated CNTs changes significantly, resulting in a high sensitivity of 23.23 kPa–1 in the low-pressure range (0.05–500 kPa) and 11.06 kPa–1 in the high-pressure range (500–1125 kPa). The sensor also exhibits outstanding sensing characteristics, including low hysteresis and excellent repeatability. Leveraging these advantages, the sensor has successfully detected pulse wave signals, neck/jaw muscle movements, and walking motions, confirming its practical applicability in wearable healthcare technologies
Recent Progress in Flexible Tactile Sensors for Human‐Interactive Systems: From Sensors to Advanced Applications
No full textConvolutional Neural Network with Biologically Inspired Retinal Structure
No full textAbstractIn this paper, we propose a new Convolutional Neural Network (CNN) with biologically inspired retinal structure and ON/OFF Rectified Linear Unit (ON/OFF ReLU). Retinal structure enhances input images by center surround difference of green-red and blue-yellow components, which in turn creates positive as well as negative features like ON/OFF visual pathway of retina to make a total of 12 feature channels. This ON/OFF concept is also adopted to each convolutional layer of CNN. We prefer to call this ON/OFF ReLU. In contrast, conventional ReLU passes only positive features of each convolutional layer and may loose important information from negative features. Moreover, it also happens to loose learning chance if results are saturated to zero. However, in our proposed model, we use both positive and negative information, which provides a possibility to learn through negative results. We also present the experimental results conducted on CIFAR-10 dataset and atrial fibrillation prediction for health monitoring, and show how effectively the negative information and retinal structure improves the performance of conventional CNN
High-Temperature-Operable Electromechanical Computing Units Enabled by Aligned Carbon Nanotube Arrays
No full textNano/micro-electromechanical
(NEM/MEM) contact switches have great
potential as energy-efficient and high-temperature-operable computing
units to surmount those limitations of transistors. However, despite
recent advances, the high-temperature operation of the mechanical
switch is not fully stable nor repetitive due to the melting and softening
of the contact material in the mechanical switch. Herein, MEM switches
with carbon nanotube (CNT) arrays capable of operating at high temperatures
are presented. In addition to the excellent thermal stability of CNT
arrays, the absence of a melting point of CNTs allows the proposed
switches to operate successfully at up to 550 °C, surpassing
the maximum operating temperatures of state-of-the-art mechanical
switches. The switches with CNTs also show a highly reliable contact
lifetime of over 1 million cycles, even at a high temperature of 550
°C. Moreover, symmetrical pairs of normally open and normally
closed MEM switches, whose interfaces are initially in contact and
separated, respectively, are introduced. Consequently, the complementary
inverters and logic gates operating at high temperatures can be easily
configured such as NOT, NOR, and NAND gates. These switches and logic
gates reveal the possibility for developing low-power, high-performance
integrated circuits for high-temperature operations
