Design of a stylus with variable tip compliance

Humans are known to modulate the impedance properties of their fingers in order to physically interact with the environment. For instance, painting or palpating fragile objects require high compliance of the fingers, while writing and measuring entails high precision position control, for which the stiffness of the fingers is increased considerably. In this thesis, we present the design, modeling, implementation, characterization and user verification of a stylus with variable tip compliance. In particular, we propose a variable stiffness mechanism as a compliant stylus that features an adjustable tip stiffness such that users can modulate compliance as needed to match the requirements of the task they perform. The variable stiffness of the stylus tip is achieved through transverse stiffness variations of axially loaded beams around their critical buckling load. Integrating an axially loaded beam with a compliant transmission mechanism, the stylus tip stiffness can be modulated over a large range. In particular, very low stiffness levels can be rendered with high fidelity, without sacrificing the mechanical integrity and load bearing capacity of the stylus. Compliant transmission mechanism of the stylus is analyzed through pseudo rigid body modeling which is a convenient and efficient way of modeling flexible elements exhibiting non-linear characteristics under large deflections. Furthermore, a novel pseudo rigid body model for a fixed-guided buckling beam that captures the iii transverse stiffness variations around the first critical buckling load is proposed and verified. These models are integrated to derive a lumped parameter model of the compliant stylus with adjustable tip stiffness. The lumped parameter model due to pseudo rigid body modeling promotes ease of analysis for design, by hiding the underlying modeling complexities of continuum mechanics from the designer. We provide experimental characterization results detailing the range of stiffness modulation achieved with several prototypes and verifying the accuracy of the equivalent pseudo rigid body model. We also present a set of human subject experiments that provide evidence in establishing the efficacy of the modulated stylus stiffness on the human performance

HySenSe: A Hyper-Sensitive and High-Fidelity Vision-Based Tactile Sensor

In this paper, to address the sensitivity and durability trade-off of Vision-based Tactile Sensor (VTSs), we introduce a hyper-sensitive and high-fidelity VTS called HySenSe. We demonstrate that by solely changing one step during the fabrication of the gel layer of the GelSight sensor (as the most well-known VTS), we can substantially improve its sensitivity and durability. Our experimental results clearly demonstrate the outperformance of the HySenSe compared with a similar GelSight sensor in detecting textural details of various objects under identical experimental conditions and low interaction forces (<= 1.5 N).Comment: Accepted to IEEE Sensors 2022 Conferenc

Classification of Colorectal Cancer Polyps via Transfer Learning and Vision-Based Tactile Sensing

In this study, to address the current high earlydetection miss rate of colorectal cancer (CRC) polyps, we explore the potentials of utilizing transfer learning and machine learning (ML) classifiers to precisely and sensitively classify the type of CRC polyps. Instead of using the common colonoscopic images, we applied three different ML algorithms on the 3D textural image outputs of a unique vision-based surface tactile sensor (VS-TS). To collect realistic textural images of CRC polyps for training the utilized ML classifiers and evaluating their performance, we first designed and additively manufactured 48 types of realistic polyp phantoms with different hardness, type, and textures. Next, the performance of the used three ML algorithms in classifying the type of fabricated polyps was quantitatively evaluated using various statistical metrics.Comment: Accepted to IEEE Sensors 2022 Conferenc

Towards Reliable Colorectal Cancer Polyps Classification via Vision Based Tactile Sensing and Confidence-Calibrated Neural Networks

In this study, toward addressing the over-confident outputs of existing artificial intelligence-based colorectal cancer (CRC) polyp classification techniques, we propose a confidence-calibrated residual neural network. Utilizing a novel vision-based tactile sensing (VS-TS) system and unique CRC polyp phantoms, we demonstrate that traditional metrics such as accuracy and precision are not sufficient to encapsulate model performance for handling a sensitive CRC polyp diagnosis. To this end, we develop a residual neural network classifier and address its over-confident outputs for CRC polyps classification via the post-processing method of temperature scaling. To evaluate the proposed method, we introduce noise and blur to the obtained textural images of the VS-TS and test the model's reliability for non-ideal inputs through reliability diagrams and other statistical metrics

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

Peer reviewe

Measurement of the Splitting Function in &ITpp &ITand Pb-Pb Collisions at root&ITsNN&IT=5.02 TeV

Data from heavy ion collisions suggest that the evolution of a parton shower is modified by interactions with the color charges in the dense partonic medium created in these collisions, but it is not known where in the shower evolution the modifications occur. The momentum ratio of the two leading partons, resolved as subjets, provides information about the parton shower evolution. This substructure observable, known as the splitting function, reflects the process of a parton splitting into two other partons and has been measured for jets with transverse momentum between 140 and 500 GeV, in pp and PbPb collisions at a center-of-mass energy of 5.02 TeV per nucleon pair. In central PbPb collisions, the splitting function indicates a more unbalanced momentum ratio, compared to peripheral PbPb and pp collisions.. The measurements are compared to various predictions from event generators and analytical calculations.Peer reviewe

Measurement of nuclear modification factors of gamma(1S)), gamma(2S), and gamma(3S) mesons in PbPb collisions at root s(NN)=5.02 TeV

The cross sections for ϒ(1S), ϒ(2S), and ϒ(3S) production in lead-lead (PbPb) and proton-proton (pp) collisions at √sNN = 5.02 TeV have been measured using the CMS detector at the LHC. The nuclear modification factors, RAA, derived from the PbPb-to-pp ratio of yields for each state, are studied as functions of meson rapidity and transverse momentum, as well as PbPb collision centrality. The yields of all three states are found to be significantly suppressed, and compatible with a sequential ordering of the suppression, RAA(ϒ(1S)) > RAA(ϒ(2S)) > RAA(ϒ(3S)). The suppression of ϒ(1S) is larger than that seen at √sNN = 2.76 TeV, although the two are compatible within uncertainties. The upper limit on the RAA of ϒ(3S) integrated over pT, rapidity and centrality is 0.096 at 95% confidence level, which is the strongest suppression observed for a quarkonium state in heavy ion collisions to date. © 2019 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3.Peer reviewe

Electroweak production of two jets in association with a Z boson in proton-proton collisions root s =13 TeV

A measurement of the electroweak (EW) production of two jets in association with a Z boson in proton-proton collisions at root s = 13 TeV is presented, based on data recorded in 2016 by the CMS experiment at the LHC corresponding to an integrated luminosity of 35.9 fb(-1). The measurement is performed in the lljj final state with l including electrons and muons, and the jets j corresponding to the quarks produced in the hard interaction. The measured cross section in a kinematic region defined by invariant masses m(ll) > 50 GeV, m(jj) > 120 GeV, and transverse momenta P-Tj > 25 GeV is sigma(EW) (lljj) = 534 +/- 20 (stat) fb (syst) fb, in agreement with leading-order standard model predictions. The final state is also used to perform a search for anomalous trilinear gauge couplings. No evidence is found and limits on anomalous trilinear gauge couplings associated with dimension-six operators are given in the framework of an effective field theory. The corresponding 95% confidence level intervals are -2.6 <cwww/Lambda(2) <2.6 TeV-2 and -8.4 <cw/Lambda(2) <10.1 TeV-2. The additional jet activity of events in a signal-enriched region is also studied, and the measurements are in agreement with predictions.Peer reviewe