Process Variations Research Articles

Comprehensive Analysis of BDS/GNSS Differential Code Bias and Compatibility Performance

High-precision DCBs are essential for effective multi-frequency and multi-constellation GNSS integration, especially in processing compatible signal observations. This study utilizes data from MGEX, iGMAS, and CORS stations to estimate and analyze long time series of BDS/GNSS DCBs, focusing on stability and influencing factors. Results indicate that DCBs for the same signal, but different channels exhibit similar ranges and trends. Among BDS DCBs, those from satellites with rubidium atomic clocks are more stable than those with hydrogen atomic clocks. An upgrade and maintenance of BDS in late 2022, reported by NABU, likely contributed to DCB jumps. BDS-compatible signal DCBs show weaker stability compared to GPS and Galileo. Variations in GNSS signal processing and receiver algorithms also impact DCB stability. Converting DCBs to OSBs and performing RMS statistics revealed that smaller differences between signals increase the susceptibility of observation equations to observation quality.

Glacial Hydro-Isostatic Adjustment at Mid-Ocean Ridges

Summary Recent studies have suggested a link between ice age sea level fluctuations and variations in magma production and crustal faulting along mid-ocean ridges based on the detection of Milankovitch cycle frequencies in topography off several ridges. These fluctuations have also been connected to variability in hydrothermal metal fluxes near ridges. Ice age sea level calculations have shown that the sea level change across glacial cycles will be characterized by significant geographic variability, that is, departures from eustasy, due to the gravitational, deformation and rotational effects of the glacial isostatic adjustment (GIA) process. Using a state-of-the-art GIA simulation that incorporates 3-D variations in Earth viscoelastic structure, including plate boundaries, and updated constraints on the magnitude and geometry of ice mass fluctuations, we predict global sea level changes from Last Glacial Maximum (LGM, 26 ka) to present and from the Penultimate Glacial Maximum (PGM, 143 ka) to the Last Interglacial (LIG, 128 ka). We focus on the results along three ridges: the Mid-Atlantic Ridge, Juan de Fuca Ridge and East Pacific Rise, which are examples of slow, intermediate and fast spreading ridges, respectively. Sea level change across the Mid-Atlantic Ridge shows the greatest variability, ranging from a sea level fall greater than 200 m in Iceland to a maximum rise of ∼150 m in the South Atlantic, with significant non-monotonicity north of the Equator as the ridge weaves across the field of sea level changes. We also calculate changes in crustal normal stress from LGM to present-day across the Mid-Atlantic and Juan de Fuca Ridges and the East Pacific Rise. These results indicate that the contribution from ice mass changes to the crustal stress field can be significant well away from the location of ancient ice complexes. We conclude that any exploration of the hypothesized links to magma production and crustal faulting must consider both ocean and ice loading effects and, more generally, the profound geographic variability of the GIA process.

Parameters of Collision and Adhesion Process Between a Rising Bubble and Quartz in Long-Chain Amine Solution and Their Correlation with Flotation

The successful adhesion of air bubbles to mineral particles is the crucial to flotation technology. This paper systematically investigates the parameters variation in the dynamic interaction process between a rising bubble and a quartz plate in long-chain amine solutions (dodecylamine, tedecylamine, and octadecylamine). The results show that the type and concentration of long-chain amine affected the collision and adhesion process between bubbles and quartz plates remarkably. The maximum rebound distance (rebound distance after the first collision) of bubbles and the stable-state liquid film thickness gradually decreases with the increase of reagent concentration. Additionally, the collision-rebound duration and induction time shorten accordingly, the surface tension of the solution decreases, the surface hydrophobicity of quartz increases, and the deformation degree and average movement velocity of bubbles decrease. With the increase in carbon chain length, the adsorption form of the amine collector and quartz surface becomes closer to vertical, and the density of water molecules decreases. The recovery of quartz particles is highest with octadecylamine systems, corresponding well with the changing trend in steady-state liquid film thickness. This research provides an effective method for in-depth analysis of the microscopic interaction mechanism between bubbles and mineral surfaces and the prediction of flotation results.

Genetic and Neuronal Basis for Facial Emotion Perception in Humans and Macaques

Abstract The ability to rapidly recognize basic facial emotions (e.g., fear) is crucial for social interactions and adaptive functioning. To date, the origin of facial emotion recognition ability remains equivocal. Using a classical twin design in humans, we found a clear dissection of low and high spatial frequencies (LSF and HSF) in facial emotion perception: whereas genetic factors contributed to individual variation in LSF processing, HSF processing is largely shaped by environmental effects. Furthermore, the ability to recognize facial emotion of LSF content genetically correlated with the function of the amygdala. Crucially, single-unit recording of the amygdala in macaques further revealed the dissociation between LSF and HSF processing in facial emotion perception, indicating the existence of an evolutionarily conserved mechanism. This cross-species study enhances insights into the neurobiological dual-route model (subcortical vs. cortical) of emotion perception and illuminates the origin and the functional development of the emotional brain in primates.

A Mura model‐based optical compensation for organic light‐emitting diode display luminance nonuniformity utilizing two image capturing

AbstractIn this paper, we proposed a new optical Mura compensation method that requires only a few Mura detections for all gray levels. We analyzed the characteristics of Mura resulting from process variations in the thin film transistor (TFT) of each pixel and developed a new model using a logarithmic function. The proposed compensation algorithm has been verified with simulation and experimental results. We found that the uniformity of the proposed compensation algorithm at 7G, 24G, 75G, 100G, 150G, and 255G, which required only two image captures, was comparable to those that required five captures. The model improved uniformity from 41.32% to 68.60% at 0.18 nit brightness, demonstrating its effectiveness. Additionally, the method significantly reduces the number of image captures needed from five to two and decreases the image capturing process time from 2183 to 150 ms, saving over 14 times in process efficiency. The proposed methodology demonstrates significant advancements in achieving luminance uniformity in OLED displays, addressing mass production constraints.

A Robust Low‐Power Power‐On‐Reset Circuit With Dual Threshold Method

ABSTRACTIn this paper, a robust low‐power power‐on‐reset (POR) circuit with dual threshold method is proposed. The current‐based circuit exhibits good robustness with respect to process, voltage, temperature, and supply ramp variations. In contrast to conventional delay‐based pulse generation approaches, a dual threshold method is introduced to generate POR and brown‐out‐reset (BOR) pulse signals, resulting in ultralow quiescent current and a compact area. Implemented in the 55‐nm CMOS process, the proposed circuit achieves an accurate trigger‐point voltage with a temperature coefficient of 90.4 ppm/°C and a deviation to the ramp time of 2.9% for a range from 100 μs to 1 s. Furthermore, the quiescent current and active area are 0.3 nA and 4834 μm2, respectively, making it particularly suitable for energy harvesting systems.

Vegetation Greening Promoted the Precipitation Recycling Process in Xinjiang

Under the combined influences of climate and vegetation change, land–atmosphere interactions have enhanced, and precipitation recycling is an important part of this. Previous studies of the precipitation recycling process have focused on calculating the precipitation recycling rate (PRR) and analyzing the influencing factors. However, the climate-driven and vegetation-induced precipitation recycling process variations were not quantified. This study has systematically examined the precipitation recycling process in a typical arid region using the Eltahir and Bras model, random forest algorithm, and partial least-squares structural equation modeling. During 1982–2018, the leaf area index (LAI) and evapotranspiration (ET) rate both increased significantly, with growth rates of 0.06 m2m−2/decade and 13.99 mm/decade, respectively. At the same time, the average PRR in Xinjiang was 13.92% and experienced significant growth at a rate of 1.28%/decade. The climate-driven and vegetation-induced PRR variations were quantified, which contributed 79.12% and 20.88%, respectively. In addition, the positive effects of both of these on PRR variations through ET did not increase with the increase in ET, but rather decreased sharply and then stabilized. This study can provide favorable theoretical support for mitigating the contradiction in water use and balancing economic development and ecological security by quantifying the regulation of precipitation by vegetation.

Controller Area Network (CAN) Bus Transceiver with Authentication Support and Enhanced Rail Converters

This paper presents an advanced Controller Area Network (CAN) bus transceiver designed to enhance security using frame-level authentication with the concept of a nonphysical virtual auxiliary data channel. We describe the newly conceived transceiver security features and provide results concerning the design, implementation, fabrication and test of the transceiver to validate its functionality and robust operation in the presence of systemic error sources including Process, Voltage, and Temperature (PVT) variations. The virtual auxiliary channel integrates CAN frame authentication signatures into the primary data payload via phase modulation while also providing compatibility with existing CAN protocols, interoperability with non-enhanced systems and requiring no network or software modifications. Enhanced rail converters are designed to facilitate single-rail to dual-rail data conversion and vice versa, preserving phase information and minimizing phase errors across various nonideal effects such as frequency drift, Process, Voltage, and Temperature (PVT) variations, and cable phase mismatch. This ensures reliable data transmission and robust authentication in the presence of adversarial cyberattacks such as packet injection. The receiver recovers both the CAN frame data and the security signature, comparing the latter with an authorized signature to provide a real-time “GO/NO_GO” signal for verifying packet authenticity and without exceeding the CAN clock jitter specifications.

Establishment and Validation of Fecal Secretory Immunoglobulin A Measurement for Intestinal Mucosal Health Assessment in Wild Lemurs.

The measurement of biomarkers in blood and excreta can enable immune status assessment and provide prognostic information on individual health outcomes. In this respect, the fecal measurement of secretory immunoglobulin A (sIgA), the primary mammalian antibody for mucosal defense, has recently received increased interest in a few anthropoid primates, but a fecal sIgA assay for use in strepsirrhine primates has not yet been reported. Here, we develop and analytically validate a cost-effective in-house sandwich enzyme immunoassay for the extraction and measurement of sIgA in feces of redfronted lemurs (Eulemur rufifrons). We also tested a simple method for sIgA extraction that can be used under remote field conditions and undertook experiments to assess the robustness of sIgA concentrations to variation in processing and storage conditions of fecal extracts. Our analytical validation revealed that the assay recognizes immunoreactive sIgA in redfronted lemur feces, that sIgA can be measured accurately with no potential interference from the fecal matrix, and that assay reagents and performance are highly stable over time. The field-friendly extraction procedure produced sIgA results strongly correlated with those generated by a standard laboratory extraction method. Short-term storage at room temperature resulted in a slight decline in sIgA concentrations, whereas freezing extracts at -20°C kept sIgA levels stable for at least 3 months. Longer-term storage of >5 months, however, led to a significant decline of sIgA concentrations. Multiple freeze-thaw cycles did not affect sIgA levels. This study, therefore, provides the basis for measuring fecal sIgA in lemurs and possibly other strepsirrhines. When samples are processed properly and stored frozen, and when sIgA analysis can be performed within 3 months upon sample collection, fecal sIgA measurements can become a valuable tool for monitoring aspects of immunity and health in both zoo-housed and wild-living lemurs.

Seed Layers for Wide-Band Gap Coevaporated Perovskite Solar Cells: CsCl Regulates Band Gap and Reduces Process Variability

Seed Layers for Wide-Band Gap Coevaporated Perovskite Solar Cells: CsCl Regulates Band Gap and Reduces Process Variability

Utilizing Spatial Statistical Bounds on Residual Stress Fields From Cold Expansion: Effects on Fatigue Crack Growth Behavior

ABSTRACTThis paper assesses the impact of utilizing statistically defined residual stress fields from cold expansion (Cx) in linear elastic, multi‐point fracture mechanics analyses using the spatial analysis of residual stress (SpARS) methodology. There is significant value and interest in leveraging the increased fatigue life afforded by Cx, but it is imperative to quantify the variability of the residual stress to understand the expected variability in benefit due to Cx. Comparisons of the predicted fatigue lives from SpARS‐produced statistical residual stress fields are made to fatigue test data. Results demonstrated that the less compressive 95% upper bound from the mean residual stress would be a reasonable strategy as it supplies a compromise between safety and inherent material and process variability while still producing a sizable improvement in predicted fatigue life. In this study, using SpARS to incorporate statistically representative residual stress fields in fatigue crack growth analyses demonstrates a methodology to aircraft structural engineers for improved fleet management and allow increased aircraft availability through fewer inspections.

Analysis of quality control in clothing production using SQC (Statistical Quality Control) and 5W+1H methods

CV Tujuh Pusaka Tala is a start-up company engaged in the clothing and sports jersey convection industry, as well as marching band musical instruments known by the brands 7MJR Store for clothing and SevenMajor for marching band musical instruments. This study was conducted to analyze the quality control of clothing production at CV. Tujuh Pusaka Tala using the Statistical Quality Control (SQC) method and the 5W and 1H approach to minimize defective products. The SQC methods used include Checksheet, Control Map, Histogram, Pareto Diagram and Cause and Effect Diagram to identify and control variability in the production process. While the 5W and 1H approach is applied to understand the main causes of product defects and find the right solution. The results of the study showed that there were 4 types of defects in the production process at CV. Tujuh Pusaka Tala, namely printing defects, screen printing defects, stitching, and material defects. The main factors causing production defects include humans, materials, machines, methods, and the environment. It can be concluded that the quality control of clothing production at CV. Tujuh Pusaka Tala using the Statistical Quality Control (SQC) method and the 5W and 1H approach to minimize defective products has been implemented well so that it can minimize the existence of defective products.

Improved of Process Production Disc Car Whell Type PSD3K (City Car Type)

This research accelerates the production process with the aim of increasing productivity from Manufacturers engaged in the manufacture of automotive parts currently experiencing an increase in sales orders on the other hand facing problems in productivity due to cracked side dies in rim production to 1400 pcs. The cracking of the side die is due to thermal shock that occurs to accelerate the production process, as a result of which cracks occur in the side die. With the concept of conducting research in the field of direct production then analyzing the characteristics of mold materials, die characteristics, process characteristics, characteristics of finished products before and after changes by testing the results of the laboratory of measuring instruments and conducting trials of variations in machine setting parameters, variations in the production process and products produced. The experiment involved changing the standard temperature from 520 °C–545 °C to 532 °C–538 °C and reducing the immersion time from a minimum of 270–540 seconds to 332 seconds. It reduces the soaking time from 69 seconds to 46 seconds and the aging time from 190 seconds to 180 seconds, increasing the casting productivity from 194,870 Pcs/28 days to 213,311 Pcs/28 days from seven machines, thus meeting the customer's requirement of 200,000 Pcs/28 days without cracking side die. Durability testing on five product samples in accordance with TSD5605G standards confirms that the quality meets customer specifications. The results of this study prove that SKD6 matrial is much stronger than FCD550 against thermal shock. Keywords: thermal shock, die disc car wheel, manufacturing, automotive parts, casting productivity

Monitoring and Interpretation of Process Variability Generated from the Integration of the Multivariate Cumulative Sum Control Chart and Artificial Intelligence

Monitoring and Interpretation of Process Variability Generated from the Integration of the Multivariate Cumulative Sum Control Chart and Artificial Intelligence

Biodegradation Study of Food Packaging Materials: Assessment of the Impact of the Use of Different Biopolymers and Soil Characteristics

In this article, the relationship between the properties of different membranes (agar, chitosan, and agar + chitosan) and biodegradability in natural and sterilized soil was investigated. The membranes under investigation exhibited variations in the biodegradation process, a phenomenon closely linked to both the soil microbiota composition and their water affinity. Higher solubility in water and greater swelling tendencies correlated with shorter initiation times for the biodegradation process in soil. Overall, all tested membranes began biodegradation within 14 days, as assessed through thickness and morphological analysis parameters, demonstrating a superior degradation rate compared to low-density polyethylene films.

A hematology-based clock derived from the Study of Longitudinal Aging in Mice to estimate biological age.

Biological clocks and other molecular biomarkers of aging are difficult to implement widely in a clinical setting. In this study, we used routinely collected hematological markers to develop an aging clock to predict blood age and determine whether the difference between predicted age and chronologic age (aging gap) is associated with advanced aging in mice. Data from 2,562 mice of both sexes and three strains were drawn from two longitudinal studies of aging. Eight hematological variables and two metabolic indices were collected longitudinally (12,010 observations). Blood age was predicted using a deep neural network. Blood age was significantly correlated with chronological age, and aging gap was positively associated with mortality risk and frailty. Platelets were identified as the strongest age predictor by the deep neural network. An aging clock based on routinely collected blood measures has the potential to provide a practical clinical tool to better understand individual variability in the aging process.

A new omnibus SPRT chart for monitoring process mean and variability based on the average number of observations to signal

The recent development of the omnibus sequential probability ratio test (OSPRT) chart marks a significant contribution to the advancement of joint monitoring schemes. As the OSPRT chart is a variable-sample-size control chart, practitioners often wish to understand its inspection efficiency, i.e. the number of observations it samples before producing a signal. In this article, we propose two enhanced optimization designs for the OSPRT chart based on the average number of observations of signal (ANOS) and expected value of the ANOS (EANOS) metrics under deterministic and unknown shift sizes, respectively. The ANOS metric is central to our design as it perfectly combines both the average run length (ARL) and the average sample number. A comparative analysis reveals that the OSPRT chart outperforms four benchmarking control charts in terms of the ANOS and EANOS metrics. Finally, an implementation of the OSPRT chart is presented with a ball shear test dataset.

Experience in developing carbonate formations with hydraulic fracturing at fields of Gazprom Neft Group

The development of carbonate formations with hydraulic fracturing is a very interesting and controversial process. In contrast to terrigenous formations, zonal stimulation can be performed by both acid and proppant fracturing methods, and the abundance of process variations expands the options even further. Although there is a general concept of choosing hydraulic fracturing technology depending on the geological and physical characteristics of the formation, the qualitative choice is complicated by the fact that effective solutions for one reservoir could not show the same efficiency in similar conditions at another one. For this reason, from the point of view of working with carbonates, to have as extensive experience as possible in various well conditions in order to minimize production risks and costs associated with the choice of approach and zonal stimulation technology. The study aims to provide a technological overview of effective fracturing solutions for carbonate formations, seeking to understand their features and applicability depending on well and geological conditions. An important place is given to the communication of experience in the application of stimulation technologies that have proven themselves at carbonate formations of Gazprom Neft and show the risks and limitations that can be encountered when choosing a particular solution. It describes experience in hydraulic and multistage fracturing, technologies, approaches and their features depending on geological conditions of carbonate formations. The study also outlines the actual experience of using hydraulic fracturing technologies at carbonate formations, their comparative effectiveness, and the most successful practices based on the actual experience of the work performed. Much attention is paid to comparing the effectiveness of acid fracturing, acid-proppant fracturing, and variations of fracturing on viscous acid compositions. The findings not only give an idea of the technological diversity of the types of zonal stimulation, but also highlights their comparative effectiveness in geological and physical conditions of the reservoir. The reflected experience can help to choose more effective solutions in the development of similar formations, reduce risks at early stages of preparation for fracturing and helps in deciding on the choice of stimulation technology, thereby improving the quality and efficiency of fields development.

Resilience evaluation of memristor based PUF against machine learning attacks

Physical unclonable functions (PUFs) have emerged as a favorable hardware security primitive, they exploit the process variations to provide unique signatures or secret keys amidst other critical cryptographic applications. CMOS-based PUFs are the most popular type, they generate unique bit strings using process variations in semiconductor fabrication. However, most existing CMOS PUFs are found to be vulnerable to modeling attacks based on machine learning (ML) algorithms. Memristors leveraging nanotechnology fabrication processes and highly nonlinear behavior became an interesting alternative to the existing CMOS-based PUF technology, introducing cryptographic and resilient random outputs. Memristor-based PUFs are emerging due to the inherent randomness at both the memristor level due to the cycle-to-cycle (C2C) programming variation of the device and the fabrication process level such as the cross-sectional area and variations. Our study focuses on building a machine learning analysis and attack framework of tools on Cu/HfO2-x/p++Si\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Cu/HfO_{2-x}/p^{++}Si$$\\end{document} memristor-based PUF (MR-PUF). Our objective is to test the resiliency of the security margins of the presented PUF using machine learning analysis tools, on-top of holistic NIST cryptographic randomness testing initially provided, to provide a high level of certainty in predicting the randomness output of the verified Memrister-based PUF. Our main contribution is a holistic study that focuses on attacking the randomness output resiliency based on building randomness predictors using Logistic Regression (LR), Support Vector Machine (SVM), Gaussian Mixture Models (GMM), K-means, K-means++\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$++$$\\end{document}, Random Forest, XGBoost and LSTM, within efficient time, and data complexity. Our results yield low accuracy and ROC results of within 0.49-0.52\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$0.49-0.52$$\\end{document} and 0.49-0.52\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$0.49-0.52$$\\end{document} respectively, indicating failure in predicting random data demonstrates efficient randomness prediction resiliency of the MR-PUF. The efficient time and data complexities of these attacks illustrated in this study are yielded to be linear and quadratic resulting in attack execution time in seconds and 5032 training samples combined with 2157 testing samples to verify the randomness of PUF.

Influence of process shifts in case of Six Sigma-based Bayesian control charts

While traditional control charts play an important role in quality assurance activities, the work on such techniques evolved over the years particularly for early detection of process shifts. Many advanced level control charts have been proposed in the literature to even detect small shifts in the process as early as possible. In order to make use of the prior beliefs and likelihood of the observed data behavior, Bayesian control charts for parameter of the posterior distribution have been proposed by various authors. The Six Sigma-based control charts ensure smaller process variations by enforcing quality improvement activities and as a result, such processes would produce higher quality products with only 3.4 defects per million opportunities (DPMO) even after allowing a shift in the process up to ± 1.5 times of process standard deviation. In this paper, an attempt has been made to develop Six Sigma-based Bayesian control charts. The proposed control charts incorporate various shift (or no-shift) combinations to prior and observed data behaviors to study their influence on the posterior parameter. Illustrative examples are also given for understanding the proposed approach. The performance evaluation and comparisons are also presented. The paper ends with a discussion and concluding remarks.