Digital Error Research Articles

Continuous-time dynamics and error scaling of noisy highly entangling quantum circuits

We investigate the continuous-time dynamics of highly-entangling intermediate-scale quantum circuits in the presence of dissipation and decoherence. By compressing the Hilbert space to a time-dependent "corner" subspace that supports faithful representations of the density matrix, we simulate a noisy quantum Fourier transform processor with up to 21 qubits. Our method is efficient to compute with a controllable accuracy the time evolution of intermediate-scale open quantum systems with moderate entropy, while taking into account microscopic dissipative processes rather than relying on digital error models. The circuit size reached in our simulations allows to extract the scaling behaviour of error propagation with the dissipation rates and the number of qubits. Moreover, we show that depending on the dissipative mechanisms at play, the choice of input state has a strong impact on the performance of the quantum algorithm.

Introduction to Semi-Classical Analysis for Digital Errors of Qubit in Quantum Processor.

In recent years, remarkable progress has been achieved in the development of quantum computers. For further development, it is important to clarify properties of errors by quantum noise and environment noise. However, when the system scale of quantum processors is expanded, it has been pointed out that a new type of quantum error, such as nonlinear error, appears. It is not clear how to handle such new effects in information theory. First of all, one should make the characteristics of the error probability of qubits clear as communication channel error models in information theory. The purpose of this paper is to survey the progress for modeling the quantum noise effects that information theorists are likely to face in the future, to cope with such nontrivial errors mentioned above. This paper explains a channel error model to represent strange properties of error probability due to new quantum noise. By this model, specific examples on the features of error probability caused by, for example, quantum recurrence effects, collective relaxation, and external force, are given. As a result, it is possible to understand the meaning of strange features of error probability that do not exist in classical information theory without going through complex physical phenomena.

Application of the digital model thermal errors of machine tools in automated production

The article presents a predicting method for a machine tool thermal error based on a nonlinear autoregressive neural network with an external input, as well as methods for smoothing experimental data obtained from measuring devices by approximation using polynomial regression and the gray systems theory. The development of accurate and robust thermal models is a critical step in achieving high productivity in thermal deformation reduction techniques on machine tools. Because thermal deformations of the machine structure caused by temperature increase often lead to thermal errors and reduce the accuracy of machining parts. The use of neural networks is a promising direction in solving forecasting problems. The authors propose a block diagram of a thermal process digital twin based on a neural network, which can be used in automated production. The results of the experiment carried out for the machine model 400V are obtained in the form of an assessment of approximation quality and accuracy of the forecasting model. The results show that the use of the proposed smoothing methods and a model for predicting a machine tool thermal error based on a neural network can improve the forecast accuracy.

A Low Power SAR ADC with Digital Error Correction Technique for Wearable and Implantable ECG Devices

Aims: This study aims to propose an 8-bit differential input low-power Successi,e Approximation Register (SAR) ADC with digital error correction technique for sensing bio-potential signals in wearable and implantable devices. Background: As dynamic comparators have the advantages of full swing output, low power consumption, high speed, and high impedance at the input, they are preferably used in energy-efficient SAR ADC’s. However, since the dynamic comparator is the most frequently used block in SAR ADC, research is ongoing to reduce its μW power further. Also, as the offset voltage of the comparator affects the linearity of ADC, it must be minimized. Linearity can further be improved by calibrating the output of ADC, and extensive surveys on the calibration methods prove that the addition- only digital error correction method is efficient in terms of power. Objective: The objective of this study is to design a low-power and low-offset dynamic comparator intended for SAR ADC to achieve highly linear digital output. In addition to this, the objective is to implement a power-efficient digital error correction technique for the output of SAR ADC to overcome the non-idealities due to process variations. Method: As power consumption is proportional to the number of transistors, the proposed comparator is a design obtaining the same output as the existing dynamic comparators with reduced transistor count. The proposed comparator, along with low power full swing three-input XOR logic gate, is implemented in SAR ADC with digital error correction technique in cadence 45 nm technology files, and its performance parameters are simulated. Results: The layout of the proposed dynamic comparator occupies an area of 3 μm2. The simulation results of this comparator with a load of 1 pF show that it has a total offset of 11.2 mV, a delay of 0.9 ns, and power consumption of 24 nW. It also achieves a gain of 49.5, i.e., 33.86 dB. The 8-bit ADC, along with the digital error correction technique operating at 143-kS/s and under 0.6 V supply voltage simulated in 45nm technology, consumes only 0.12 μW of power. The DNL and INL errors obtained are +0.22/-0.2 LSB and -0.28 LSB, respectively. SNR limited by noise is 48.25 dB, SFDR is 48.64 dB, and ENOB achieved is 7.72. Conclusion: To satisfy the requirement of the wearable and implantable devices, a low-power SAR ADC with good linearity is designed using a low-power and low-offset dynamic comparator. A digital error correction technique using a low-power XOR logic gate is implemented at the SAR ADC output to minimize the non-idealities due to the process variations.

Parametrized Hamiltonian simulation using quantum optimal control

Analog quantum simulation offers a hardware-specific approach to studying quantum dynamics, but mapping a model Hamiltonian onto the available device parameters requires matching the hardware dynamics. We introduce a paradigm for quantum Hamiltonian simulation that leverages digital decomposition techniques and optimal control to perform analog simulation. We validate this approach by constructing the optimal analog controls for a superconducting transmon device to emulate the dynamics of an extended Bose-Hubbard model. We demonstrate the role of control time, digital error, and pulse complexity, and we explore the accuracy and robustness of these controls. We conclude by discussing the opportunity for implementing this paradigm in near-term quantum devices.

A super-grayscale and real-time computer-generated Moir\xe9 profilometry using video grating projection

By using the time-division multiplexing characteristics of the projector and the integral exposure characteristics of the charge coupled device (CCD) camera, a super-grayscale and real-time computer-generated Moiré profilometry based on video grating projection is proposed. The traditional digital static grating is of 256-grayscale at most. If an expected super-grayscale grating with a maximum grayscale of 766 is designed and divided into three 256-grayscale fringe patterns with balanced grayscale as far as possible, they can be synthesized into a repeated playing video grating instead of the traditional static grating. When the video grating is projected onto the measured object, as long as the exposure time is set to three times the refresh cycle of the video grating, the super-grayscale deformed patterns in the 766-grayscale can be captured with a 10-bit CCD camera, so that the deformed patterns are realistic. The digital error in computer-generated Moiré profilometry is effectively reduced. In addition, this method can expand the linear range of the deformed pattern by 20% in computer Moiré profilometry. Therefore, the proposed method has the perspectives of high accuracy and real-time measurement. Theoretical analysis and experimental results demonstrate the validity and capability of the proposed method.

Secret messaging with endogenous chemistry

Data encoded in molecules offers opportunities for secret messaging and extreme information density. Here, we explore how the same chemical and physical dimensions used to encode molecular information can expose molecular messages to detection and manipulation. To address these vulnerabilities, we write data using an object’s pre-existing surface chemistry in ways that are indistinguishable from the original substrate. While it is simple to embed chemical information onto common objects (covers) using routine steganographic permutation, chemically embedded covers are found to be resistant to detection by sophisticated analytical tools. Using Turbo codes for efficient digital error correction, we demonstrate recovery of secret keys hidden in the pre-existing chemistry of American one dollar bills. These demonstrations highlight ways to improve security in other molecular domains, and show how the chemical fingerprints of common objects can be harnessed for data storage and communication.

Abstract 543: ctDNA MRD detection from plasma and urine and personalized oncogenomic analysis in oligometastatic colorectal cancer

Abstract BACKGROUND: Circulating tumor DNA (ctDNA) can detect molecular residual disease (MRD) in plasma after curative-intent treatment of non-metastatic solid tumor malignancy when prior mutational knowledge from either tumor or pre-treatment plasma is available. We hypothesized that ctDNA MRD analysis without prior mutational knowledge could be performed to assess oligometastatic colorectal cancer (CRC) treated with curative intent by applying an error-corrected ultra-deep targeted sequencing approach. We also investigated urine as an alternative analyte for ctDNA MRD detection in this non-genitourinary setting. METHODS: We applied AVENIO, a ctDNA technology derived from CAncer Personalized Profiling by deep Sequencing (CAPP-Seq) with integrated digital error suppression (iDES), to plasma, tumor, and urine samples acquired on the day of surgery from 24 prospectively enrolled oligometastatic CRC patients. We sequenced patients' white blood cell DNA to remove age-related clonal hematopoiesis variants. Plasma and urine ctDNA MRD detection were then correlated with residual disease present in tumor tissue, and adjuvant treatment strategies were proposed based on plasma ctDNA-inferred tumor mutational burden and targetable genomic alterations. RESULTS: Tumor-naïve plasma ctDNA analysis detected MRD at a median level of 0.62% with 95% sensitivity and 100% specificity. Plasma ctDNA MRD levels correlated with tumor size at the time of surgery (ρ= 0.68, P = 0.0003) and were significantly lower in patients without evidence of disease in their surgical specimen compared to those with residual tumor cells (P = 0.02). In urine, ctDNA MRD detection specificity remained high at 100%, but sensitivity was lower at 64%, with median levels being 11-fold lower than in plasma (P < 0.0001). Cell-free DNA fragments containing mutations were shorter in urine with an average size of 150.1 bp, compared to 180.2 bp in plasma (P < 0.0001). Personalized ctDNA MRD oncogenomic analysis revealed that 81% of patients had a high inferred tumor mutational burden (>10 mutations/megabase), and 10% also had a targetable PIK3CA mutation. CONCLUSION: Tumor-naïve plasma ctDNA analysis can sensitively and specifically detect MRD in patients with oligometastatic CRC after neoadjuvant chemotherapy. Urine-based ctDNA MRD detection is also feasible in these patients; however, it is less sensitive than plasma. Analysis of oligometastatic CRC patients' ctDNA MRD also revealed potentially actionable results that might have implications for personalized adjuvant treatment regimens. Citation Format: Bruna Pellini, Nadja Pejovic, Wenjia Feng, Noah Earland, Peter K. Harris, Abul Usmani, Jeffrey J. Szymanski, Farid Qaium, Jacqueline Mudd, Hyun Kim, Benjamin Tan, Ryan C. Fields, Aadel A. Chaudhuri. ctDNA MRD detection from plasma and urine and personalized oncogenomic analysis in oligometastatic colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 543.

Phase-stable repetition rate multiplication of dual-comb spectroscopy based on a cascaded Mach-Zehnder interferometer.

In this Letter, we demonstrate a passive all-fiber pulse delay method for repetition rate multiplication of dual-comb spectroscopy. By combining a cascaded Mach-Zehnder interferometer and digital error correction, a mode-resolved spectrum with improved acquisition speed and sensitivity can be obtained. This technique has the strengths of compact, broadband, high energetic efficiency, and low complexity. Due to the use of an adaptive post-processing algorithm, sophisticated closed-loop feedback electronics are not required, which provides a simple and effective scheme to break through the physical limitation of the repetition frequency of the frequency comb for phase-stable dual-comb applications.

Quantifying clinical severity of physics errors in high-dose rate prostate brachytherapy using simulations

PURPOSETo quantitatively evaluate through automated simulations the clinical significance of potential high-dose rate (HDR) prostate brachytherapy (HDRPB) physics errors selected from our internal failure-modes and effect analysis (FMEA). METHODS AND MATERIALSA list of failure modes was compiled and scored independently by 8 brachytherapy physicists on a one-to-ten scale for severity (S), occurrence (O), and detectability (D), with risk priority number (RPN) = SxOxD. Variability of RPNs across observers (standard deviation/average) was calculated. Six idealized HDRPB plans were generated, and error simulations were performed: single (N = 1722) and systematic (N = 126) catheter shifts (craniocaudal; -1cm:1 cm); single catheter digitization errors (tip and connector needle-tips displaced independently in random directions; 0.1 cm:0.5 cm; N = 44,318); and swaps (two catheters swapped during digitization or connection; N = 528). The deviations due to each error in prostate D90%, urethra D20%, and rectum D1cm3 were analyzed using two thresholds: 5–20% (possible clinical impact) and >20% (potentially reportable events). RESULTSTwenty-nine relevant failure modes were described. Overall, RPNs ranged from 6 to 108 (average ± 1 standard deviation, 46 ± 23), with responder variability ranging from 19% to 184% (average 75% ± 30%). Potentially reportable events were observed in the simulations for systematic shifts >0.4 cm for prostate and digitization errors >0.3 cm for the urethra and >0.4 cm for rectum. Possible clinical impact was observed for catheter swaps (all organs), systematic shifts >0.2 cm for prostate and >0.4 cm for rectum, and digitization errors >0.2 cm for prostate and >0.1 cm for urethra and rectum. CONCLUSIONSA high variability in RPN scores was observed. Systematic simulations can provide insight in the severity scoring of multiple failure modes, supplementing typical FMEA approaches.

NPM1 Mutated AML Can Relapse with Wildtype NPM1 and Evolve with Novel Mutations: Implications for Pathobiology and MRD Monitoring

Introduction: Minimal residual disease (MRD) monitoring by qPCR is feasible in AML with mutated NPM1 (NPM1 mut ) . NPM1 mut leukemia is associated with a favorable outcome and MRD negativity is associated with an excellent prognosis. Cytogenetic and molecular analysis have proven the concept of clonal evolution in relapsed or refractory AML. Data is conflicting on NPM1 mut AML relapsing with wildtype NPM1 (NPM1 negative). In this study we analyzed 105 relapsed NPM1 mut AML patients including 15/105 patients that relapsed with NPM1 negative AML.Aims: To analyze in patients with NPM1 mut AML the frequency and mutational landscape of NPM1 negative AML at relapse and provide insight into clonal evolution.Patients and Methods: Between 2006 und 2017 we investigated a total of 105 intensively treated patients with NPM1 mut AML who attained a complete molecular remission (CMR) and finally relapsed. MRD was monitored by qPCR at 1394 consecutive time points (median=12 per patient, range 3-42). 15/105 patients experienced a NPM1 negative relapse. Unique molecular identifier based sequencing of 63 genes associated with hematological malignancies was performed for patients with NPM1 negative relapse in paired samples at diagnosis and at clinical relapse. The median coverage was 4,900x. Digital error suppression was applied to follow mutations in up to 1/500 molecules (VAF 0.2%).Results: For 15 patients with an NPM1 negative relapse the median time to relapse was 39 months (range 4-66). In contrast for 90/105 patients with an NPM1 mut relapse the median time to relapse was significantly shorter with 14 months (range 3-77, p=0.005). We analyzed the overall survival (OS) following relapse. For patients with NPM1 negative relapse OS at 2 years was 48% [95% CI, 12-77] versus 68% [52-79] for patients with NPM1 mut relapse (n.s.).For 61/90 patients with NPM1 mut relapse the diagnostic sample was available for analysis with the 63 gene panel. The mutational landscape of these patients revealed recurrent co-mutations in 14 different genes in 54/61 patients, with the published pattern: DNMT3A, TET2, FLT3- ITD, NRAS, SRSF2, IDH1, IDH2 and FLT3- TKD were affected in more than 10% of cases. A median of 2 genes were co-mutated per patient, no co-occurring mutation was found in only 7/61 patients (11%).For 12/15 cases with NPM1 negative relapse both diagnostic and relapse samples were available for 63 gene panel sequencing. At diagnosis we identified a total of 33 co-mutations in addition to NPM1 in a total of 12 different genes in 12/12 patients (DNMT3A (n=9 ), TET2 (6), IDH1 (4), SRSF2 (3), PTPN11 (2), IDH2 (1), KRAS (1), NRAS (1), EZH2, (1), STAG2 (1), ASXL1 (1) and FLT3- TKD (1)). All patients had at least one co-mutation with a median of 2 co-mutations per patient at diagnosis (range 1-6). At relapse we identified a total of 37 co-mutations in 13 different genes in 11/12 patients with a median of 2 mutations per patient (range 0-6). Eleven mutations in 9 genes (TET2, STAG2, PTPN11, SRSF2, KRAS, DNMT3A, EZH2, FLT3- TKD and NRAS) ) were lost at relapse and 15 mutations in 10 genes (TP53, RUNX1, NRAS, NF1, IDH2, SRSF2, WT1, IDH1, EZH2, TET2) were gained at relapse. We used digital error correction to reassess these mutations in the diagnostic sample. With a detection limit of up to 0.2% VAF (1/500 molecules) none of these mutations was detectable at diagnosis. DNMT3A was the most prevalent mutation (9/12 at diagnosis, 7/12 at relapse) and compared to the cohort with NPM1 mut relapse the presence of a DNMT3A mutation was associated with NPM1 negative relapse (p=0.024).One patient (8%) relapsed with the respective ancestral clone from diagnosis (w/o NPM1), 9 patients (75%) showed a relapse with the known ancestral clone plus evolution, and 2 patients (17%) relapsed with a completely unrelated clone.Conclusion: We identified 14% of NPM 1mut AML patients who relapsed with an NPM1 negative AML following intensive therapy. NPM1 negative relapse occurs significantly later than NPM1 mut relapse and is associated with the ancestral clone in the majority of patients. NPM1 negativity at relapse evades MRD assessment, however mutations in the ancestral clone should be detectable by NGS with digital error correction. This could be included in an extended MRD monitoring strategy, and performed in addition to qPCR for NPM1 at the routine time points. DisclosuresHöllein:MLL Munich Leukemia Laboratory: Employment. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Fasan:MLL Munich Leukemia Laboratory: Employment. Dicker:MLL Munich Leukemia Laboratory: Employment. Jeromin:MLL Munich Leukemia Laboratory: Employment. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

In Depth Molecular Characterization of AML with RUNX1-RUNX1T1 at Diagnosis and Relapse

Introduction: Minimal residual disease (MRD) monitoring by qPCR is feasible in AML with RUNX1-RUNX1T1 fusion. The absence of RUNX1-RUNX1T1 transcripts is considered as complete molecular remission (CMR). Risk stratification according to MRD is possible and initial studies allocating MRD positive patients to allogeneic stem cell transplantation have been undertaken (Zhu et al., Blood 2013). However, despite CMR about 10% to 30% of patients relapse. In our cohort 90/130 AML patients with RUNX1-RUNX1T1 fusion reached CMR. We analyzed all 17/90 that relapsed following CMR.Aims: To analyze the frequency, the clinical parameters and the mutational landscape of RUNX1-RUNX1T1 positive AML relapsing after CMR and to gain insights into the clonal evolution.Patients and Methods: Between 2005 und 2017 we investigated a total of 130 intensively treated AML patients with RUNX1 - RUNX1T1 fusion at diagnosis and at least two follow up samples. We applied quantitative real-time PCR to detect RUNX1-RUNX1T1 / ABL1 ratios with a sensitivity of 0.001%. We identified 17 patients with relapse following CMR and used unique molecular identifier (UMI) based gene panel sequencing to analyze the clonal architecture and evolution of this cohort in comparison to paired results at diagnosis. UMIs were used for digital error suppression to detect minimal variant allele fractions (VAFs) of up to 0.2%.Results: CMR was reached in 90/130 pts (69%) after a median of 5 months (range 5-45 months). Median event free survival (EFS) of patients with CMR was not reached (EFS at 2 years 82%). However, 17/90 (19%) relapsed during follow up with a median time to relapse of 13 months after CMR (range 4 to 38 months). The ratio of RUNX1-RUNX1T1 / ABL1 was 2.1 fold higher at diagnosis than at relapse with a median of 80 (range 4-508) versus 40 (range 2-501) respectively (n.s.).For all 17 cases who relapsed following CMR the diagnostic and relapse samples were subject to sequencing of 63 genes known to be mutated in hematologic neoplasms. At diagnosis we identified a total of 27 somatic mutations in 11 different genes co-occurring with RUNX1-RUNX1T1 in 14/17 patients: ASXL1 (n=6 ), ASXL2 (5), KIT (5), NRAS (2), CSF3R (2), FLT3- TKD (2), FLT3- ITD (1), IDH2 (1), KRAS (1), TET2 (1), RAD21 (1), SRSF2 (1). The median number of mutations per patient was 2 (range 0-5). At relapse we identified a total of 13 mutations in 7 different genes in 8/17 patients. 18 mutations in 9 genes (ASXL2, ASXL1, KIT, NRAS, CSF3R, FLT3-TKD, KRAS, RAD21, SRSF2) were lost at relapse and 4 mutations in 3 genes (KIT, PHF6, TET2)were gained at relapse. The median number of mutations per patient at relapse was significantly reduced: Fourteen patients (82%) had at least one mutation at diagnosis and only 9 patients (53%) at relapse (p=0.026). The median variant allele fraction (VAF) of co-occurring mutations at diagnosis was 24% (range 1-24) and 42% (range 3-67) at relapse (1.7 fold, n.s.). Changes in VAF did not reveal an evident general principle, however in some cases the gene with the highest VAF at diagnosis disappeared at relapse suggestive of the selection of a subclone.When analyzed for clonal evolution 13/17 patients (76%) showed a clonal change at relapse: nine of 17 patients (53%) relapsed with an ancestral clone, 3 (17%) with an ancestral clone with evolution and one (6%) with the initial clone with evolution. Four of 17 patients (24%) relapsed with the initial clone.As control we sequenced the diagnostic sample in 42/90 patients who did not relapse following CMR. A total of 30 mutations were found in 9 genes in 21/42 patients (median=0.5): ASXL2 (25%), TET2 (11%), KIT (10%), NRAS (10%), FLT3- ITD (6%), CBL (5%), ASXL1 (5%), FLT3- TKD (2%), IDH2 (2%). When compared to the 17 patients with relapse following CMR, the presence of an ASXL1 (p=0.0172) mutation at diagnosis and the total number of mutations at diagnosis (median=2 versus median=0.5; p=0.0024) were significantly associated with relapse.Conclusion: We analyzed the clonal evolution of RUNX1-RUNX1T1 positive AML following CMR. We observed losses and gains of mutations at relapse, but the majority of cases showed a reduction of numbers of mutations. This underscores that RUNX1-RUNX1T1 fusion is the key driver aberration and stable over time. However mutations in ASXL1 and the number of co-mutations at diagnosis is significantly associated with relapse following CMR. This should be considered when tailoring treatment strategies. DisclosuresHöllein:MLL Munich Leukemia Laboratory: Employment. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Fasan:MLL Munich Leukemia Laboratory: Employment. Jeromin:MLL Munich Leukemia Laboratory: Employment. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

Mechanical behavior predictions of additively manufactured microstructures using functional Gaussian process surrogates

Relational linkages connecting process, structure, and properties are some of the most sought after goals in additive manufacturing (AM). This is desired especially because the microstructural grain morphologies of AM components can be vastly different than their conventionally manufactured counterparts. Furthermore, data collection at the microscale is costly. Consequently, this work describes and demonstrates a methodology to link microstructure morphology to mechanical properties using functional Gaussian process surrogate models in a directed graphical network capable of achieving near real-time property predictions with single digit error magnitudes when predicting full stress–strain histories of a given microstructure. This methodology is presented and demonstrated using computationally generated microstructures and results from crystal plasticity simulations on those microstructures. The surrogate model uses grain-level microstructural descriptors rather than whole microstructure descriptors so that properties of new, arbitrary microstructures can be predicted. The developed network has the potential to scale to predict mechanical properties of grain structures that would be infeasible to simulate using finite element methods.

Assessing Accuracy of Land Cover Change Maps Derived from Automated Digital Processing and Visual Interpretation in Tropical Forests in Indonesia

This study assessed the accuracy of land cover change (2000–2018) maps compiled from Landsat images with either automated digital processing or with visual interpretation for a tropical forest area in Indonesia. The accuracy assessment used a two-stage stratified random sampling involving a confusion matrix for assessing map accuracy and by estimating areas of land cover change classes and associated uncertainty. The reference data were high-resolution images from SPOT 6/7 and high-resolution images finer than 5 m obtained from Open Foris Collect Earth. Results showed that the map derived from automated digital processing had lower accuracy (overall accuracy 73–77%) compared to the map based on visual interpretation (overall accuracy 80–84%). The automated digital processing map error was in differentiating between native forest and plantation areas. While the visual interpretation map had a higher accuracy, it did not consistently differentiate between native forest and shrub areas. Future improvement of the digital map requires more accurate differentiation between forest and plantation to better support national forest monitoring systems for sustainable forest management.

A fast simulation method for analysis of SEE in VLSI

The transistor simulation tools (e.g. TCAD and SPICE) are widely used to simulate single event effects (SEE) in industry. However, due to the variances of the physical parameters in practical design, e.g. the nature of the particle, linear energy transfer and circuit characteristics would have a large impacts on the final simulation accuracy, which will significantly increase the complexity and cost in the workflow of the transistor level simulation for large scale circuits. Therefore, a new SEE simulation scheme is proposed to offer a fast and cost-efficient method to evaluate and compare the performance of large scale circuits in the effects of radiation particles. In this work, we have combined both the advantages of transistor and hardware description language (HDL) simulations, and proposed accurate SEE digital error models for high-speed error analysis in the large scale circuits. The experimental results show that the proposed scheme is able to handle SEE simulations for more than 40 different circuits with the sizes varied from 100 transistors to 100 k transistors.

A digital and structure-adaptive geometric error definition and modeling method of reconfigurable machine tool

Reconfigurable machine tool (RMT) is designed for mass customization machining and the structure is reconfigured unpredictably due to the wide range of requirements. After reconstruction, accuracy of the new machine tool must be guaranteed firstly, which puts forward higher requirements of flexibility for error definition and modeling. Therefore, a digital and structure-adaptive geometric error definition and modeling method is presented to quickly respond to the structure changes of RMT. The highlight of this method is that the definition and modeling of geometric errors can be realized automatically. Firstly, a coding method is proposed to express the machine tool component with structure and motion information so that the geometric error definition and modeling can be computerized. Then, common expression of the geometric errors considered kinematic and structural attributes is presented. The identification coefficient matrix of geometric error is defined and calculated by using an assignment algorithm according to the configuration tree. At last, geometric error modeling modules are defined and sequential multiplication calculation is presented to establish the geometric error model automatically. Three typical examples are illustrated to verify the correction of digital method. It is the basis of intelligent error compensation of RMT under the market environment of changing demands.

Identification of sustainable control and digital dimension errors in business organizations

In recent years, the technique of centralized control of complex production processes has moved from the stage of development and experimentation to widespread industrial implementation. Centralized control equipment is used in large, complex objects, and the control systems themselves are so complex that they cannot be calculated or reasonably selected using the methods used for conventional control and measuring equipment. The work undertaken recently in order to create various calculation methods for centralized control systems, at best, solved individual particular problems, often from different initial positions, and, apparently, there was a need for generalizing work that would give the system designers centralized control is an efficient settlement tool. Of the technical characteristics of centralized control systems, the most essential and most fully reflecting the effectiveness of their operation is accuracy, especially if this concept is broadly approached, including any deviation from the required system behavior in the error. Centralized control systems are used in various fields: to control production processes, for scientific research, including space objects, for testing and researching technical structures, for monitoring the health of complex equipment. These applications have a number of similarities and, however, differ in the number of requirements put forward by individual applications. When writing the article, the main attention was paid to centralized control systems for continuous production processes, which, in contrast to a number of testing and research systems, are characterized by the duration of action, since the production processes themselves in most cases run continuously for many hours, days or even months.

La estética del error en el diseño gráfico contemporáneo: conexiones entre el glitch, la cultura posdigital y el New Ugly

En el marco de la comunicación visual actual, se observa una proliferación de singulares prácticas cuya orientación estética está basada en la imperfección como ingrediente fundamental. En este contexto, la investigación busca revelar la presencia del error digital en el diseño gráfico contemporáneo, concretamente, mediante el análisis de dos líneas principales (cuya relación se trata de demostrar): por una parte, la cultura posdigital y dos de sus ramificaciones (el universo posinternet y la Nueva Estética), conceptos que sido estudiados casi exclusivamente desde el arte para explicar la invasión de motivos digitales y tecnológicos, la fusión de los mundos físico y virtual o un escenario definido por la progresiva pérdida de seducción por parte del Internet; y, por otro lado, el New Ugly, una ecléctica corriente de diseño gráfico que encuentra en la simulación amateur su principal rasgo diferencial. Mediante la revisión bibliográfica como método principal, apoyada en una muestra intencional, no probabilística, de imágenes de proyectos de diseño gráfico que procuran justificar el vínculo entre los anteriores enfoques, las conclusiones apuntan a una importante presencia del error digital en el diseño gráfico actual y a la conexión entre el New Ugly y la cultura posdigital mediante el glitch como eslabón estético.

Explanatory defect causation model linking digital innovation, human error and quality improvement in residential construction

This paper examines the role of mobile digital technology in improving quality in housing construction, specifically by reducing defects at handover. Many construction technology impact studies are limited: confined to studying the effects of new technologies in controlled prototype-testing settings, framed around overly broad claims, or built on deterministic propositions assuming that technology unproblematically leads to better quality. Current studies also ignore insights from defect causation models that systematically identify sources of errors and defects. This study's aim was to develop an explanatory defect causation model addressing all four limitations. The proposed model, developed though a qualitative case study involving 10 semi-structured interviews and two phases of analysis, comprises 16 conditions linked in non-deterministic relationships of influence. The model contributes to theory in housing construction management by proposing alternative complex pathways which link defects, technology and quality and can be translated into actionable, flexible strategies for addressing defects in practice.

A 77.1-dB-SNDR 6.25-MHz-BW Pipeline SAR ADC With Enhanced Interstage Gain Error Shaping and Quantization Noise Shaping

This article presents an enhanced interstage gain error shaping (GES) technique that adopts a digital error feedback (DEF) method to address the truncation error in the prior implementation, which can extend the interstage gain error tolerance by five times. The proposed DEF technique does not introduce additional errors as it operates purely in the digital domain. This article also proposes a first-order passive quantization noise shaping (NS) technique that reduces the input-pair ratio of the two-input-pair comparator by 2.7 times, thus alleviating the noise penalty caused by using a multiple-input-pair comparator. A prototype analog-to-digital converter (ADC) equipped with the proposed techniques in a 40-nm CMOS technology achieves a 77.1-dB signal-to-noise-and-distortion ratio (SNDR) over 6.25-MHz bandwidth while operating at 100 MS/s and consuming 1.38 mW. It achieves a 173.7-dB Schreier figure of merit (FoM).