Alignment Procedure Research Articles

Single input state, single mode fiber based spectral domain polarization sensitive optical coherence tomography using a single linear-in-wavenumber spectral camera

A single input state, single mode fiber (SMF) based spectral domain polarization sensitive optical coherence tomography (SD-PS-OCT) system using a single linear-in-wavenumber spectral camera is presented. With the proposed dual channel linear-in-wavenumber spectral camera and the polarization alignment procedure, the orthogonal polarization components of the spectral interference signal can be detected using the all SMF based SD-PS-OCT system without any bulk polarization optical elements. To evaluate the performance of the developed system, the polarization properties of a Babinet-Soleil compensator and a quarter waveplate are quantitatively measured with high accuracy. Furthermore, the depth-resolved images of the intensity, the phase retardation and the optic axis orientation of the ex-vivo tendon tissue and the chicken muscle tissue are reconstructed to verify the feasibility of the proposed method.

IPBAvizu: a PyMOL plugin for an efficient 3D protein structure superimposition approach

BackgroundProtein 3D structure is the support of its function. Comparison of 3D protein structures provides insight on their evolution and their functional specificities and can be done efficiently via protein structure superimposition analysis. Multiple approaches have been developed to perform such task and are often based on structural superimposition deduced from sequence alignment, which does not take into account structural features. Our methodology is based on the use of a Structural Alphabet (SA), i.e. a library of 3D local protein prototypes able to approximate protein backbone. The interest of a SA is to translate into 1D sequences into the 3D structures.ResultsWe used Protein blocks (PB), a widely used SA consisting of 16 prototypes, each representing a conformation of the pentapeptide skeleton defined in terms of dihedral angles. Proteins are described using PB from which we have previously developed a sequence alignment procedure based on dynamic programming with a dedicated PB Substitution Matrix. We improved the procedure with a specific two-step search: (i) very similar regions are selected using very high weights and aligned, and (ii) the alignment is completed (if possible) with less stringent parameters. Our approach, iPBA, has shown to perform better than other available tools in benchmark tests. To facilitate the usage of iPBA, we designed and implemented iPBAvizu, a plugin for PyMOL that allows users to run iPBA in an easy way and analyse protein superimpositions.ConclusionsiPBAvizu is an implementation of iPBA within the well-known and widely used PyMOL software. iPBAvizu enables to generate iPBA alignments, create and interactively explore structural superimposition, and assess the quality of the protein alignments.

Track based alignment procedure for the CBM silicon tracking detector

The CBM (Compressed Baryonic Matter) experiment at FAIR is being designed for the study of the QCD phase diagram in the region of the high baryon chemical potential at relatively moderate temperatures. The Silicon Tracking System (STS) is the central detector for momentum reconstruction of the produced charged particles in the CBM experiment. It consists of 8 layers of altogether ∼ 900 double sided silicon micro strip sensors. Limited mechanical precision(> 100μm) during the mounting, temperature differences during the experiment, influence of the applied magnetic field result in misalignment to the detector component positions. Therefore, the intrinsic spatial resolution(∼ 20μm) of the detector components has to be recovered by a track based alignment method. In this conference paper, the current status of implementation of the alignment algorithm is presented. For this work, the GBL (General broken line) track refit model is employed to create the necessary input data structure to provide the input to the standalone PEDE part of the χ2 minimization based MILLEPEDE II alignment algorithm.

Synthesizing Facial Photometries and Corresponding Geometries Using Generative Adversarial Networks

Artificial data synthesis is currently a well-studied topic with useful applications in data science, computer vision, graphics, and many other fields. Generating realistic data is especially challenging, since human perception is highly sensitive to non-realistic appearance. In recent times, new levels of realism have been achieved by advances in GAN training procedures and architectures. These successful models, however, are tuned mostly for use with regularly sampled data such as images, audio, and video. Despite the successful application of the architecture on these types of media, applying the same tools to geometric data poses a far greater challenge. The study of geometric deep learning is still a debated issue within the academic community, as the lack of intrinsic parametrization inherent to geometric objects prohibits the direct use of convolutional filters, a main building block of today’s machine learning systems. In this article, we propose a new method for generating realistic human facial geometries coupled with overlayed textures. We circumvent the parametrization issue by utilizing a specialized non-rigid alignment procedure, and imposing a global mapping from our data to the unit rectangle. This mapping enables the representation of our geometric data as regularly sampled 2D images. We further discuss how to design such a mapping to control the distortion and conserve area within the target image. By representing geometric textures and geometries as images, we are able to use advanced GAN methodologies to generate new plausible textures and geometries. We address the often-neglected topic of relationship between texture and geometry and propose different methods for fitting generated geometries to generated textures. In addition, we widen the scope of our discussion and offer a new method for training GAN models on partially corrupted data. Finally, we provide empirical evidence demonstrating our generative model’s ability to produce examples of new facial identities, independent from the training data, while maintaining a high level of realism—two traits that are often at odds.

Uncertainties in the Power Alignment at the Jordan Research and Training Reactor

Nuclear research reactors are required to be equipped with an active Reactor Protection System (RPS) that intervenes and shuts down the reactor at pre-set trip set-points, assuring that the reactor operating conditions do not exceed safety limits stated in the reactor Safety Analysis Report (SAR). However, for the RPS to truly prevent the reactor power from exceeding the reactor power safety limits, robust and accurate calibration of the RPS power signals is required.The accuracy of the power alignment at the Jordan Research and Training Reactor (JRTR) was evaluated by estimating sources of uncertainty in the measured thermal power, most significantly induced by assumptions in the thermal power evaluation method, and by the uncertainties in temperature and flow rate measurements.Based on the results of the analyses, a set of recommended modifications to the power alignment procedure and to the Operator Work Stations (OWS) alarm set points are provided to ensure that the RPS satisfies its function of shutting down the reactor without exceeding the safety limits.

Pixels and 3-D Points Alignment Method for the Fusion of Camera and LiDAR Data

The fusion of light detection and ranging (LiDAR) and camera data is a promising approach to improve the environmental perception and recognition for intelligent vehicles because of the combination of depth and color information. One of the difficulties in achieving the fusion is the accurate alignment of the 3-D points with the image pixels. Current methods of data alignment involve the steps of estimating the camera intrinsic parameters and developing a transformation matrix between the camera and LiDAR frame. The drawback of these methods is the accumulation of errors during the calculation of the camera intrinsic parameters and the transformation matrix. In order to improve the data alignment accuracy, we propose a novel algorithm that directly calculates the alignment between the 3-D points and the pixels without the need for camera parameters and calibration of the coordinate transformation matrix. We call the proposed method the pixel and 3-D point alignment (PPA) method. The alignment procedure is achieved by using the extracted corresponding points. First, we calculate a linear alignment matrix without considering the image distortion; and second, we optimize the parameters using the maximum likelihood estimation to consider the camera distortion. Simulation and experimental results indicate that the PPA method is able to align the 3-D points in LiDAR frame with the pixels in image frame with higher accuracy and increased robustness against noise in calibration process than comparable state-of-the-art methods.

Iterative Optimization-Based ISAR Imaging With Sparse Aperture and Its Application in Interferometric ISAR Imaging

Recently, high-resolution inverse synthetic aperture radar (ISAR) imaging with sparse aperture (SA) data has attracted increasing attention. The theory of compressive sensing (CS) suggests that an unknown sparse signal can be accurately recovered by taking advantage of very limited samples. For ISAR images, the number of the resolution cells occupied by the strong scattering points of the target is usually much smaller than that of the resolution cells of the image plane, revealing the strong sparsity trait of the ISAR signal. This trait of ISAR signal creates the conditions for incorporating CS into high-resolution ISAR imaging. In this paper, a novel iterative optimization-based SA-ISAR imaging approach is proposed. First, the SA-ISAR signal model is established and the envelope alignment is executed on the one-dimensional range profiles of the SA data. Next, the gradient-based algorithm is exploited to recover the complete signals. Then, by iteratively performing the procedures of the envelope alignment and the signal recovery, the accuracy of signal recovery can be significantly improved and a high-quality ISAR image can be obtained. Ultimately, the extension of the iterative optimization-based SA-ISAR imaging to the three-dimensional (3-D) interferometric ISAR (InISAR) imaging is successfully implemented via the traditional ISAR imagery pair interferometric method. The experiments based on the measured and simulated data are carried out to validate the superiority of the novel algorithm.

Refocusing of Ground Moving Target in Circular Synthetic Aperture Radar

Due to the non-cooperative motion of ground moving targets, they appear smeared and dislocated in circular synthetic aperture radar (CSAR) imagery. Refocusing of ground moving target in CSAR is a challenging problem because of the circular trajectory of the radar platform and unknown motion parameters of ground moving targets. In this paper, an inverse SAR (ISAR) technique-based method with Legendre polynomial approximation for ground moving target refocusing in CSAR is proposed. Different from the conventional ISAR-based method, the method extracts range migration of the moving target in the range-frequency domain directly, which can avoid the range alignment procedure in conventional ISAR techniques. Furthermore, the Legendre polynomial approximation is applied to fit the extracted range migration, which can be carried out iteratively to fulfill the requirement of accuracy. The experimental CSAR data processing results show that the proposed method can achieve satisfied imaging quality of ground moving targets.

High precision automated alignment procedure for two-mirror telescopes.

A significant challenge in the production of Earth observation satellites is the precise alignment of the telescope optical components. We have developed a strategy to perform automated alignment of two-mirror telescopes for use in a realistic factory-based setting. A Ritchey-Chrétien telescope was used as an example. The secondary mirror was mounted on a high precision hexapod and its misalignment inferred from the Zernike coefficients for tilt, defocus, and coma, as measured by a phase-shifting interferometer. The required corrections to the position of the secondary mirror were implemented using an integral controller and alignment was achieved within minutes, compared to within days when using a manual alignment process. The Zernike coefficient for each aberration was reduced to within one standard deviation of the fluctuations due to residual instability (48nm).

Unsupervised Phonetic Segmentation of Classical Arabic Speech Using Forward and Inverse Characteristics of the Vocal Tract

Automatic segmentation of speech is about identifying boundaries of phonemes in a given utterance. This paper presents a strategy driven by cosine distance similarity scores for identifying phoneme boundaries. The proposed strategy helps in the selection of appropriate feature extraction technique for speech segmentation applications. After assessing various state-of-the-art speech processing techniques, a novel combination of forward and inverse characteristics of vocal tract (FICV) is developed. The proposed technique is evaluated on Classical Arabic dataset. Extensive experiments are made to compare the proposed technique with state-of-the-art techniques, including the hidden Markov model-based forced alignment procedures. The results show that proposed technique has total error rate of 14.48%, while the accuracy is 85.2% within 10 ms alignment error. When compared with the existing state-of-the-art technique, the proposed technique outperforms by 12.29% and 22.73% in terms of error rates and alignment accuracies, respectively, which signifies the potential of using FICV in speech segmentation.

1H NMR spectroscopy combined with multivariate data analysis for differentiation of Brazilian lager beer according to brewery

In this study, 1H NMR spectroscopy was used to classify samples of beer, considering three categories (Ambev, Heineken, and Grupo Petropolis), employing chemometric methods: principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and soft independent modeling of class analogies (SIMCA). The full NMR spectra were evaluated, although only the aliphatic region (0–3 ppm) was used for multivariate analysis, since it provided superior results, compared to the use of other regions or the full spectrum. It was necessary to use an alignment procedure to eliminate small deviations in the chemical shifts caused by variations of pH and intermolecular interactions. Organic acids (lactic, acetic, and succinic acids) were the chemical compounds most susceptible to these variations. In the PCA, the first two components explained 82.1% of the variability of the dataset, while PLS-DA and SIMCA both provided accuracy higher than 92% in the prediction sets.

Non-paraxial design and fabrication of a compact OAM sorter in the telecom infrared

A novel optical device is designed and fabricated in order to overcome the limits of the traditional sorter based on log-pol optical transformation for the demultiplexing of optical beams carrying orbital angular momentum (OAM). The proposed configuration simplifies the alignment procedure and significantly improves the compactness and miniaturization level of the optical architecture. Since the device requires to operate beyond the paraxial approximation, a rigorous formulation of transformation optics in the non-paraxial regime has been developed and applied. The sample has been fabricated as 256-level phase-only diffractive optics with high-resolution electron-beam lithography, and tested for the demultiplexing of OAM beams at the telecom wavelength of 1310 nm. The designed sorter can find promising applications in next-generation optical platforms for mode-division multiplexing based on OAM modes both for free-space and multi-mode fiber transmission.

Data-driven cross-talk modeling of beam losses in LHC collimators

The Large Hadron Collider at CERN is equipped with a collimation system to intercept potentially dangerous beam halo particles before they damage its sensitive equipment. The collimator settings are determined following a beam-based alignment procedure, in which the collimator jaws are moved towards the beam until losses appear in the beam loss monitors. When the collimator reaches the beam envelope, beam losses propagate mainly in the direction of the beam and are, therefore, also observed by other nearby beam loss monitors. This phenomenon is known as cross talk. Due to this, collimators are aligned sequentially to be able to identify which losses are generated by which collimator, such that any cross talk across beam loss monitors positioned close to each other is avoided. This paper seeks to quantify the levels of cross-talk observed by beam loss monitors when multiple collimators are moving, to be able to determine the actual beam loss signals generated by their corresponding collimators. The results obtained successfully predicted the amount of cross-talk observed for each of the cases tested in this study. This was then extended to predict loss map case studies and the proton impacts at each collimator by comparing them to simulations.

Strapdown Inertial Navigation System Initial Alignment Based on Modified Process Model

In this paper, the nonlinear initial alignment method for Strapdown inertial navigation system is investigated. As an important part of the nonlinear initial alignment method, the dynamic model based on nonlinear error equations is re-derived with the consideration of the mismatch between the calculated navigation frame and the actual navigation frame. Then, the recursive nonlinear initial alignment procedure based on the modified model under the marine mooring condition is elaborated. The superiority of the proposed method over traditional method in terms of rapidness, accuracy, and consistency is validated through simulated and experimental tests.

A fast alignment method for grating-based X-ray phase-contrast imaging systems

The alignment of a grating-based X-ray phase-contrast interferometer is an iterative process that requires numerous steps of changing the distances and angles between the gratings. For each alignment step an image is acquired to evaluate the detected intensity signature in order to optimize the observed moir'e pattern. Thus, a large number of images has to be taken for the alignment procedure. This is not feasible within reasonable time at X-ray sources like X-ray backlighters where the time between two X-ray shots is on the scale of hours. Here, we report on the development of a stable and transportable setup ready-to-use for grating-based X-ray phase-contrast imaging. A comprehensive set of reference images taken at a continuous beam serves as a look-up table which enables the grating alignment within very few alignment steps. Since this method features a fast, reliable and predictable alignment, it is also beneficial for grating-based X-ray phase-contrast imaging systems at common X-ray sources.

A robust and fast self-alignment method for strapdown inertial navigation system in rough sea conditions

In this paper, a robust and fast self-alignment method under an undesirable non-periodic unidirectional vessel motion is proposed. The proposed method is based on the attitude determination technique which transforms the alignment procedure into an attitude determination problem by creating infinite vector observations. The method implements the QUaternion ESTimator (QUEST) attitude determination technique which reduces the computational complexity in practical implementations and accomplishes the alignment task more robustly and accurately compared with the Kalman filter based alignment methods in a specific time interval. Simulation and also experimental results show that the proposed technique has more accurate and faster responses compared to the conventional methods based on the Kalman filter. • Introducing a vessel motion derived from experience during self-alignment of SINS. • Overcoming the challenge of self-alignment by creating vector observations. • Low computational complexity for attitude determination by using vector observations. • The robustness of the proposed method against the disturbing forces. • Obtaining the vector observations for compensation of the Lever Arm effect.

Alignment as an Alternative to Anchor Purification in DIF Analyses

Unbalanced differential item functioning (DIF) occurs when the items favoring group 1 are not balanced by items favoring group 2. This creates false differences in the total score used for matching examinee subgroups or inaccuracy in the scaling used to bring the groups to commensurable metrics. Historically, unbalanced DIF has been addressed by removing DIF items from the set of anchor items, often called purification. A recently developed alignment procedure minimizes the impact of the DIF items in scaling the groups without removing them. In this study, when the data followed a two-parameter model, the results using alignment or a purified anchor were generally comparable when the DIF was balanced or when the DIF was unbalanced but no more than 20% of the items contained DIF. With a larger percentage of unbalanced DIF, the alignment procedure yielded more accurate estimates of the group means and the magnitude of the DIF.

Instrument predevelopment activities for FLEX mission

The fluorescence imaging spectrometer (FLORIS) is the payload of the fluorescence explorer mission (FLEX) of the European Space Agency. The mission objective is to perform quantitative measurements of the solar-induced vegetation fluorescence aiming at monitoring photosynthetic activity. FLORIS works in a push-broom configuration, and it is designed to acquire data in the 500 to 780 nm spectral range with a sampling of 0.1 nm in the oxygen bands (759 to 769 nm and 686 to 697 nm) and 0.5 to 2.0 nm in the red edge, chlorophyll absorption, and photochemical reflectance index bands. FLEX will fly in formation with Sentinel-3 to benefit from the measurements made by Sentinel-3 instruments, OLCI, and SLSTR, particularly concerning the cloud screening, the proper characterization of the atmospheric state, and the determination of the surface temperature. The instrument concept is based on a common telescope and two modified Offner spectrometers with reflective concave gratings both for the high resolution (HR) and low resolution (LR) spectrometers. In the frame of the instrument predevelopment, Leonardo Company (Italy) has built and tested an elegant breadboard of the instrument consisting of the telescope and the HR spectrometer. OHB System AG (Germany) is in charge of the development of the LR spectrometer. The main objectives of the activity are to anticipate the development of the instrument and provide early risk retirement of the critical components; evaluate the system performances such as imaging quality parameters, straylight, ghost, polarization sensitivity, and environmental influences; verify the adequacy of critical tests such as spectral characterization and straylight; and define and optimize instrument alignment procedures. Following a brief overview of the FLEX mission, we will cover the design and the development of the optics breadboard with emphasis on the results obtained during the tests and the lessons learned for the flight unit.

Image-based autofocusing system for nonlinear optical microscopy with broad spectral tuning.

We present an image-based autofocusing system applied in nonlinear microscopy and spectroscopy with a wide range of excitation wavelengths. The core of the developed autofocusing system consists of an adapted two-step procedure maximizing an image score with six different image scorings algorithms implemented to cover different types of focusing scenarios in automated regime for broad wavelength region. The developed approach is combined with an automated multi-axis alignment procedure. We demonstrate the key abilities of the autofocusing procedure on different types of structures: single nanoparticles, nanowires and complex 3D nanostructures. Based on these experiments, we determine the optimal autofocusing algorithms for different types of structures and applications.

A method for aligning the plastic scintillator detector on DAMPE

The Plastic Scintillator Detector (PSD) onboard the DArk Matter Particle Explorer (DAMPE) is designed to measure cosmic ray charge (Z) and to act as a veto detector for gamma ray identification. To fully exploit the charge identification potential of PSD and to enhance its capability to identify gamma ray events, we develop an alignment method for the PSD. The path length of a given track in the volume of a PSD bar is derived taking into account the shift and rotation alignment corrections. By examining energy spectra of corner-passing events and fully contained events, position shifts and rotations of all PSD bars are obtained, and are found to be on average about 1mm and 0.0015 radian respectively. To validate the alignment method, we introduce artificial shifts and rotations of PSD bars into the detector simulation. These shift and rotation parameters can be recovered successfully by the alignment procedure. As a result of the PSD alignment procedure, the charge resolution of the PSD is improved from 4% to 8%, depending on the nuclei.