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1. Milling Stability Modeling by Sample Partitioning with Chatter Frequency-Based Test Point Selection

   https://doi.org/10.3390/jmmp8030109  

   Schmitz, Tony (June 2024, Journal of Manufacturing and Materials Processing)

   This paper describes a sample partitioning approach to retain or reject samples from an initial distribution of stability maps using milling test results. The stability maps are calculated using distributions of uncertain modal parameters that represent the tool tip frequency response functions and cutting force model coefficients. Test points for sample partitioning are selected using either (1) the combination of spindle speed and mean axial depth from the available samples that provides the high material removal rate, or (2) a spindle speed based on the chatter frequency and mean axial depth at that spindle speed. The latter is selected when an unstable (chatter) result is obtained from a test. Because the stability model input parameters are also partitioned using the test results, their uncertainty is reduced using a limited number of tests and the milling stability model accuracy is increased. A case study is provided to evaluate the algorithm. 

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2. Sample-to-sample correspondence for unsupervised domain adaptation

   https://doi.org/https://doi.org/10.1016/j.engappai.2018.05.001  

   Das, Debasmit; Lee, C.S. George (May 2018, Engineering applications of artificial intelligence)

   The assumption that training and testing samples are generated from the same distribution does not always hold for real-world machine-learning applications. The procedure of tackling this discrepancy between the training (source) and testing (target) domains is known as domain adaptation. We propose an unsupervised version of domain adaptation that considers the presence of only unlabelled data in the target domain. Our approach centres on finding correspondences between samples of each domain. The correspondences are obtained by treating the source and target samples as graphs and using a convex criterion to match them. The criteria used are first-order and second-order similarities between the graphs as well as a class-based regularization. We have also developed a computationally efficient routine for the convex optimization, thus allowing the proposed method to be used widely. To verify the effectiveness of the proposed method, computer simulations were conducted on synthetic, image classification and sentiment classification datasets. Results validated that the proposed local sample-to- sample matching method out-performs traditional moment-matching methods and is competitive with respect to current local domain-adaptation methods. 

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3. A label efficient two-sample test

   Li, W.; Dasarathy, G.; Ramamurthy, K. N.; Berisha, V. (January 2022, Thirty-Eighth Conference on Uncertainty in Artificial Intelligence)

   Two-sample tests evaluate whether two samples are realizations of the same distribution (the null hypothesis) or two different distributions (the alternative hypothesis). We consider a new setting for this problem where sample features are easily measured whereas sample labels are unknown and costly to obtain. Accordingly, we devise a three-stage framework in service of performing an effective two-sample test with only a small number of sample label queries: first, a classifier is trained with samples uniformly labeled to model the posterior probabilities of the labels; second, a novel query scheme dubbed bimodal query is used to query labels of samples from both classes, and last, the classical Friedman-Rafsky (FR) two-sample test is performed on the queried samples. Theoretical analysis and extensive experiments performed on several datasets demonstrate that the proposed test controls the Type I error and has decreased Type II error relative to uniform querying and certainty-based querying. Source code for our algorithms and experimental results is available at https://github.com/wayne0908/Label-Efficient-Two-Sample. 

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4. A portable impedance microflow cytometer for measuring cellular response to hypoxia

   https://doi.org/10.1002/bit.27879  

   Dieujuste, Darryl; Qiang, Yuhao; Du, E. (July 2021, Biotechnology and Bioengineering)

   Abstract This article presents the development and testing of a low‐cost (<$60), portable, electrical impedance‐based microflow cytometer for single‐cell analysis under a controlled oxygen microenvironment. The system is based on an AD5933 impedance analyzer chip, a microfluidic chip, and an Arduino microcontroller operated by a custom Android application. A representative case study on human red blood cells (RBCs) affected by sickle cell disease is conducted to demonstrate the capability of the cytometry system. Impedance values of sickle blood samples exhibit remarkable deviations from the common reference line obtained from two normal blood samples. Such deviation is quantified by a conformity score, which allows for the measurement of intrapatient and interpatient variations of sickle cell disease. A low conformity score under oxygenated conditions or drastically different conformity scores between oxygenated and deoxygenated conditions can be used to differentiate a sickle blood sample from normal. Furthermore, an equivalent circuit model of a suspended biological cell is used to interpret the electrical impedance of single flowing RBCs. In response to hypoxia treatment, all samples, regardless of disease state, exhibit significant changes in at least one single‐cell electrical property, that is, cytoplasmic resistance and membrane capacitance. The overall response to hypoxia is less in normal cells than those affected by sickle cell disease, where the change in membrane capacitance varies from −23% to seven times as compared with −17% in normal cells. The results reported in this article suggest that the developed method of testing demonstrates the potential application for a low‐cost screening technique for sickle cell disease and other diseases in the field and low‐resource settings. The developed system and methodology can be extended to analyze cellular response to hypoxia in other cell types. 

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5. Exploiting Switching of Transistors in Digital Electronics for RFID Tag Design

   C-L Cheng, L. N. (June 2019, IEEE journal of radio frequency identification)

   Existing analog-signal side-channels, such as EM emanations, are a consequence of current-flow changes that are dependent on activity inside an electronic circuits. In this paper, we introduce a new class of side-channels that is a consequence of impedance changes in switching circuits, and we refer to it as an impedance-based side-channel. One example of such a side-channel is when digital logic activity causes incoming EM signals to be modulated as they are reflected (backscattered), at frequencies that depend on both the incoming EM signal and the circuit activity. This can cause EM interference or leakage of sensitive information, but it can also be leveraged for RFID tag design. In this paper, we first introduce a new class of side-channels that is a consequence of impedance differences in switching circuits, and we refer to it as an impedance-based side-channel. Then, we demonstrate that the impedance difference between transistor gates in the high-state and in the low-state changes the radar cross section (RCS) and modulates the backscattered signal. Furthermore, we have investigated the possibility of implementing the proposed RFID on ASIC for signal enhancement. Finally, we propose a digital circuit that can be used as a semi-passive RFID tag. To illustrate the adaptability of the proposed RFID, we have designed a variety of RFID applications across carrier frequencies at 5.8 GHz, 17.46 GHz, and 26.5 GHz to demonstrate flexible carrier frequency selection and bit configuration. 

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