Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis and quantification of device spectral signatures observed using a spectroscopic photon emission microscope

Two normalisation methods have been introduced for the analysis and quantification of device spectral signatures obtained from the spectroscopic photon emission microscope (SPEMS). The parameter: /spl lambda//sub 1.0/ and /spl lambda//sub 50%/, having clear spectral distribution for different devices or mechanisms involved, were found to be useful in device failure analysis. It is also found that these wavelength parameters are dependent on the internal electric fields of the device. Hence, these can be used as an alternative method of monitoring electric fields in devices.
An isolated-open pattern to de-embed pad parasitics [CMOSFETs]

To meet radio frequency (RF) performance required in large market of wireless applications, CMOS transistors having a small unit gate width are preferred. To correctly estimate RF performance, parasitics of the on-wafer pads and interconnection metal lines should be de-embedded as in the advanced bipolar transistors. However, cutoff frequencies of small-size MOSFETs de-embedded by the conventional on-wafer dummy structures result in large overestimation. A new open pattern is proposed to solve the problem. The meaning and justification of the new de-embedding pattern are discussed.
N-Dimensional Principal Component Analysis

In this paper, we first briefly introduce the multidimensional Principal Component Analysis (PCA) techniques, and then amend our previous N-dimensional PCA (ND-PCA) scheme by introducing multidirectional decomposition into ND-PCA implementation. For the case of high dimensionality, PCA technique is usually extended to an arbitrary n-dimensional space by the Higher-Order Singular Value Decomposition (HO-SVD) technique. Due to the size of tensor, HO-SVD implementation usually leads to a huge matrix along some direction of tensor, which is always beyond the capacity of an ordinary PC. The novelty of this paper is to amend our previous ND-PCA scheme to deal with this challenge and further prove that the revised ND-PCA scheme can provide a near optimal linear solution under the given error bound. To evaluate the numerical property of the revised ND-PCA scheme, experiments are performed on a set of 3D volume datasets.
APPLICATION OF DEEP RESIDUAL NETWORK IN FAULT DIAGNOSIS OF PHOTOVOLTAIC MODULES

Fault diagnosis techniques can accurately determine the health condition of photovoltaic modules, as well as the specific fault type and level. Conventional machine learning diagnosis algorithms rely on expert knowledge and manual feature extraction to build feature engineering, which usually leads to limited performance. In addition, the existing fault diagnosis methods of photovoltaic modules have a limitation. They only take the influence of the area size of fault array into account when determining the fault level, and ignore the effect caused by the degree of fault factor itself. In view of the above problems, this paper proposes a fault diagnosis method of photovoltaic modules based on deep residual network, which can automatically extract useful fault features. Raw current-voltage characteristic curves and ambient conditions are used as the input of the network. To verify the effectiveness of the proposed methodology, two datasets are obtained based on a laboratory experiment platform and the corresponding simulation model respectively. Furthermore, five popular machine learning methods, including support vector machine, decision tree, random forest and two other convolution neural networks, are used for comparison. According to the results, the proposed method achieves better comprehensive performance with the highest diagnostic accuracy and convergence speed.
Hybridized off-line 2-MHz zero-current-switched quasi-resonant converter

Thick-film hybrid technology is used to develop a half-bridge, half-wave, zero-current-switched quasi-resonant converter for 300 V DC offline application. With a conversion frequency of 2 MHz the converter delivers 80 W at 78% efficiency with a power density, excluding heat sink, of 21 W/in/sup 3/. The operation and detailed electrical and hybrid design of the circuit are described. Also described is a 2 MHz hybridized gate drive. >
The Deep Capsule Prior – advantages through complexity?

In inverse problems, an extensive number of ground truth samples for the training of supervised deep learning models is seldom available. Unsupervised approaches, like the Deep Image Prior, offer a valuable alternative in this case. In our work, we combine the idea of the Deep Image Prior with recently proposed capsule networks. The new model is tested against a standard convolutional Deep Image Prior on different image processing tasks and computed tomography reconstruction.
Valuing the Greenhouse Gas Emissions from Wind Power

This study concludes that much can be gained from harmonisation of historic life cycle estimates and moving towards a standard approach for carbon assessment of given technologies should be seen as an industry imperative. Wind power estimates lying within the interquartile range of meta-analyses such as presented in this paper and elsewhere should be considered to be reliable. However, the effects of wind generation intermittency on the carbon efficiency of thermal generation plant elsewhere in a supply network is not fully quantified and must be investigated to improve our knowledge of the overall carbon emissions produced by the deployment of wind generation plant.
An Assessment of Meteorological Effects on Air Quality in Windsor, Ontario, Canada - Sensitivity to Temporal Modeling Resolution

The HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) model was used to study air quality in the City of Windsor (42.16° N, 82.58° W), Ontario, Canada. Two-day back trajectory simulations were conducted for the year of 2003 to investigate the regional transport of air pollutants. Trajectories were then characterized by air mass path direction and regions traversed as dominant factors in regional transport of air pollutants, to assess meteorological effects on air quality in Windsor and provide initial identification of potential upwind pollution source regions. Statistical analysis was conducted to study whether the trajectory simulation results are sensitive to temporal modeling resolution of one, two, three and six simulations per week. It was found that HYSPLIT backward trajectory modeling can provide good quality and consistent results with a temporal resolution of two or three runs per week, comparable to a resolution of six runs per week. The HYSPLIT backward trajectory modeling and analysis methods presented can identify potential source regions of transboundary pollutants at practical temporal modeling resolutions. This is useful to communities and policy-makers developing public health policy.
Non‐reflecting tapered slotline antenna with linear phase responses of both reflection and transmission for short‐pulse applications

A non‐reflecting tapered slotline antenna (NRTSA) with linear phase responses of both reflection and transmission is proposed in this article. The non‐reflecting characteristic is achieved by designing a resistive and reactive loading network, which could effectively absorb the non‐radiated reflected signals and transmit the pulse with little distortion simultaneously. The integration of the loading network and the tapered slotline antenna enables the NRTSA to realize the linear phase responses of both port reflection and pulse transmission. Also, the time‐domain reflection and radiation performance of the NRTSA excited by a short‐pulse are investigated. A prototype was fabricated to verify the antenna performance. The measured results show that the NRTSA features a −9‐dB impedance bandwidth from DC to 16 GHz (200%), a peak realized gain of 9.36 dBi, a maximal cross‐polarization level of −14.8 dB (2.5–16 GHz), and a waveform fidelity of 0.95 when transmitting a Gaussian pulse with a spectrum from 4.5 GHz to 12.5 GHz. Both the non‐reflecting characteristic and short‐pulse transmission performance of the NRTSA enable it to be favorable for ultra‐wideband short‐pulse applications.
Reducing Set Retardation in High-Volume Fly Ash Mixtures with the Use of Limestone

High-volume fly ash (HVFA) concretes are attractive not only because they reduce cement content and the associated greenhouse gases, but also because they avoid landfilling excessive quantities of fly ash. These sustainability benefits are often tempered by practical constructability limitations that may exist for HVFA concretes: retardation and diminution of the early-age reaction, delay in setting (and finishing operations), and lower early-age strength. This paper explores the alleviation of these deficiencies in HVFA mixtures by the incorporation of fine limestone powders into ternary blends. Isothermal calorimetry and Vicat needle penetration measurements are employed to assess reaction rates and setting times, respectively. A systematic variation of the content and fineness of the limestone powder in mixtures containing either a Class C or a Class F fly ash indicates that setting times are linearly correlated with the surface area supplied by the limestone. Comparison of a limestone system to a system containing an inert titanium dioxide of similar particle size indicates that the acceleration and amplification effects of the limestone can be attributed to both physical (nucleation) and chemical (additional calcium ions) processes. The results indicate that ternary blends with 40% of the cement by volume replaced by 30% to 35% fly ash and 5% to 10% limestone at a constant water volume fraction can be achieved without significant delay in setting.
Competitiveness in construction: a critical review of research

Since its popularization in the 1980s, competitiveness has received close attention from practitioners and researchers across a wide range of industries. In the construction sector, many works on competitiveness have also been published. So far, however, there seems to be no comprehensive review to summarize and critique existing research on competitiveness in construction. This research, therefore, reviews the extant literature from four aspects: concept of competitiveness, competitiveness research at the construction industry level, competitiveness research at the firm level, and competitiveness research at the project level. The review presents the state‐of‐the‐art development of competitiveness research in construction, identifies the research gaps, and proposes new directions for further studies. Further research is recommended to validate previous studies in construction practices, identify the mechanisms that encourage mutual enhancement of competitiveness at different levels, and how to achieve its sustainability by embracing new management and/or economics techniques.
Functional impairment of CD19+CD24hiCD38hi B cells in neuromyelitis optica spectrum disorder is restored by B cell depletion therapy

Description Defective regulatory B cells that contribute to autoimmunity are recovered by B cell depletion therapy in patients with NMOSD. Restoring regulatory B cells Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune disease of the central nervous system driven by pathogenic B cells. Clinical studies have shown that B cell depletion therapy (BCDT) is an effective treatment. However, the impact of BCDT on regulatory B (Breg) cells, which produce IL-10 and suppress inappropriate immune responses, is not clear. Here, Kim et al. evaluated Breg cells isolated from patients before and after BCDT. They found that patients with NMOSD had fewer Breg cells and that those cells were dysfunctional. BCDT restored Breg cell numbers and partially rescued their suppressive capacity. These findings suggest that the therapeutic benefit of BCDT goes beyond simply depleting pathogenic B cells. The role of B cells in immune response regulation is context dependent. In some cases, bystander B cell activation leads to interleukin-10 (IL-10) production, suppressing inappropriate immune responses. However, the role of B cells in regulation of autoimmune diseases, including neuromyelitis optica spectrum disorder (NMOSD), is incompletely understood. NMOSD is an autoimmune disease of the central nervous system with a relapsing-remitting course in which acute attacks lead to severe disability. B cell depletion therapy (BCDT) has shown clinical efficacy in NMOSD by eliminating pathogenic B cells; however, its effect on regulatory B (Breg) cells remains elusive. Here, we evaluated the B cell subsets, Breg cell function, and the effect of BCDT on these cells in patients with NMOSD. We showed that CD24hiCD38hi B cells from patients with NMOSD did not inhibit CD4+ T cell production of interferon-γ (IFN-γ), IL-17, or IL-21 and failed to inhibit follicular helper T cell expansion or induce regulatory T cells. This cellular impairment in patients with NMOSD can be explained by deficient Breg cell numbers and Breg cell–intrinsic deficits in IL-10 production specifically in response to B cell bystander activation. Using cross-sectional and 3-year longitudinal studies, we showed that BCDT treatment restored the numerical deficiency of Breg cells. Moreover, the post-BCDT repopulated CD24hiCD38hi B cells restored IL-10 production and suppressed IFN-γ and IL-17 production by CD4+ T cells. Our results suggest that both numerical deficiency of CD24hiCD38hi B cells and their impaired regulatory function contribute to NMOSD pathophysiology, and function is restored after BCDT.
Three-phase Single Switch Power Factor Correction Circuit with Harmonic Reduction

A harmonic injection technique, which reduces the line frequency harmonics of the single switch three-phase boost rectifier, has been implemented. In this method, a periodic voltage is injected in the control circuit to vary the duty cycle of the rectifier switch within a line cycle so that the fifth-order harmonic of the input current is reduced to meet the total harmonic distortion (THD) requirement. Since the injected voltage signal, which is proportional to the inverted ac component of the rectified three-phase line-to-line input voltages is employed; the injected duty cycle variations are naturally synchronized with the three-phase line-to- neutral input voltages.
Wave dispersion in high‐rise buildings due to soil–structure interaction

Nonparametric techniques for estimation of wave dispersion in buildings by seismic interferometry are applied to a simple model of a soil–structure interaction (SSI) system with coupled horizontal and rocking response. The system consists of a viscously damped shear beam, representing a building, on a rigid foundation embedded in a half‐space. The analysis shows that (i) wave propagation through the system is dispersive. The dispersion is characterized by lower phase velocity (softening) in the band containing the fundamental system mode of vibration, and little change in the higher frequency bands, relative to the building shear wave velocity. This mirrors its well‐known effect on the frequencies of vibration, i.e. reduction for the fundamental mode and no significant change for the higher modes of vibration, in agreement with the duality of the wave and vibrational nature of structural response. Nevertheless, the phase velocity identified from broader band impulse response functions is very close to the superstructure shear wave velocity, as found by an earlier study of the same model. The analysis reveals that (ii) the reason for this apparent paradox is that the latter estimates are biased towards the higher values, representative of the higher frequencies in the band, where the response is less affected by SSI. It is also discussed that (iii) bending flexibility and soil flexibility produce similar effects on the phase velocities and frequencies of vibration of a building. Copyright © 2014 John Wiley & Sons, Ltd.
A novel single composite Shewhart‐EWMA control chart for monitoring the process mean

Statistical process monitoring (SPM) literature recommends the combination of Shewhart and exponentially weighted moving average (EWMA) schemes to improve the ability of the standalone Shewhart and EWMA monitoring schemes in detecting small to large shifts. The resulting scheme is named combined (or composite) Shewhart‐EWMA (CSEWMA) scheme. In this paper, a new single composite Shewhart‐EWMA (denoted as SCSEWMA) scheme for monitoring the mean when the process parameters are known or unknown is proposed using an additive weighted model. The flexibility of the proposed scheme is made possible by an additional weighing parameter that regulates its sensitivity towards shifts of different sizes. The new scheme is compared to the existing Shewhart, EWMA and CSEWMA X¯$\bar X$ schemes, and the results reveal the superiority of the proposed scheme over the latter schemes. Simulated and real‐life data are used to demonstrate the application and implementation of the proposed scheme.
Model identification and controller design of a fish-like robot

Robotic fish is an interesting and prospective subject to develop. The simplest fish swimming mode to be mimicked for fish robots is the ostraciiform mode which only requires caudal fin flapping. An almost submerged ostraciiform fish robot was constructed to study its swimming characteristics. The swimming direction can be controlled by changing the mean angle of caudal fin oscillation. Experiments were conducted to study the behavior of the fish robot and in particular, the transfer function between swimming path angular rate and mean angle of the caudal fin oscillation were identified. Error to signal ratio quantity was used to determine how well the model fits with the experimental data. This identification model was used to design a 2-degree-of-freedom PID controller that meets some specific requirements to improve the steering performance.
Deforestation Detection with Fully Convolutional Networks in the Amazon Forest from Landsat-8 and Sentinel-2 Images

The availability of remote-sensing multisource data from optical-based satellite sensors has created new opportunities and challenges for forest monitoring in the Amazon Biome. In particular, change-detection analysis has emerged in recent decades to monitor forest-change dynamics, supporting some Brazilian governmental initiatives such as PRODES and DETER projects for biodiversity preservation in threatened areas. In recent years fully convolutional network architectures have witnessed numerous proposals adapted for the change-detection task. This paper comprehensively explores state-of-the-art fully convolutional networks such as U-Net, ResU-Net, SegNet, FC-DenseNet, and two DeepLabv3+ variants on monitoring deforestation in the Brazilian Amazon. The networks’ performance is evaluated experimentally in terms of Precision, Recall, F1-score, and computational load using satellite images with different spatial and spectral resolution: Landsat-8 and Sentinel-2. We also include the results of an unprecedented auditing process performed by senior specialists to visually evaluate each deforestation polygon derived from the network with the highest accuracy results for both satellites. This assessment allowed estimation of the accuracy of these networks simulating a process “in nature” and faithful to the PRODES methodology. We conclude that the high resolution of Sentinel-2 images improves the segmentation of deforestation polygons both quantitatively (in terms of F1-score) and qualitatively. Moreover, the study also points to the potential of the operational use of Deep Learning (DL) mapping as products to be consumed in PRODES.
Robust hand gesture detection by fusion of depth and colour information using kinect

Microsoft Kinect camera has drastically changed the world of human computer interaction based computer vision, due to its low cost and high quality of depth information for visual images. This has made the depth data to become common place at a very low cost allowing myriad of computer vision related application including hand gesture recognition. Hand gesture recognition research suffered severely from the clutter and skin tone regions in any background. With the availability of depth information, background clutter and skin toneregions which are not part of the hand gesture can be removed improving the performance of any classification strategy. This article discusses a novel hand detection strategy based on Kinect camera by combining depth and colour image information. In the detection procedure, the Kalman filter is applied to the study to achieve a good detection result. The experiment results show this detection method is reliable and stable in the clutter background, and works well in various light conditions.
Using conceptual tool for intuitive interaction to design intuitive website for SME in India : A case study

Statistical reports of SMEs Internet usage from various countries indicate a steady growth. However, deeper investigation of SME’s e-commerce adoption and usage reveals that a number of SMEs fail to realize the full potential of e-commerce. Factors such as lack of tools and models in Information Systems and Information Technology for SMEs, and lack of technical expertise and specialized knowledge within and outside the SME have the most effect. This study aims to address the two important factors in two steps. First, introduce the conceptual tool for intuitive interaction. Second, explain the implementation process of the conceptual tool with the help of a case study. The subject chosen for the case study is a real estate SME from India. The design and development process of the website for the real estate SME was captured in this case study and the duration of the study was four months. Results indicated specific benefits for web designers and SME business owners. Results also indicated that the conceptual tool is easy to use without the need for technical expertise and specialized knowledge.
Modelling of settling and flocculation of fine sediments in still water

A numerical model to predict settling behaviour of fine sediment mixtures in a stagnant water column is described. Both single-grain settling mode and the floc settling mode are considered. The single-grain settling mode is analyzed by solving the unsteady, one-dimensional diffusion–advection equation numerically and the floc settling mode is examined by solving a coagulation equation expressed as a discrete equation in logarithmic radius space considering the differential settling as the only collision mechanism. The model results are compared with the laboratory experimental data of K. Kranck for both modes of sediment settling. The agreement between the model predictions and the experimental data is good. The model can be used as a basis for such practical applications as predicting sedimentation rates in reservoirs and settling basins. Key words: sediment mixtures, settling, flocculation, advection, diffusion, floc size distribution, primary particles.