Fast Alignment Method Research Articles

An integration of fast alignment and maximum-likelihood methods for electron subtomogram averaging and classification.

MotivationCellular Electron CryoTomography (CECT) is an emerging 3D imaging technique that visualizes subcellular organization of single cells at sub-molecular resolution and in near-native state. CECT captures large numbers of macromolecular complexes of highly diverse structures and abundances. However, the structural complexity and imaging limits complicate the systematic de novo structural recovery and recognition of these macromolecular complexes. Efficient and accurate reference-free subtomogram averaging and classification represent the most critical tasks for such analysis. Existing subtomogram alignment based methods are prone to the missing wedge effects and low signal-to-noise ratio (SNR). Moreover, existing maximum-likelihood based methods rely on integration operations, which are in principle computationally infeasible for accurate calculation.ResultsBuilt on existing works, we propose an integrated method, Fast Alignment Maximum Likelihood method (FAML), which uses fast subtomogram alignment to sample sub-optimal rigid transformations. The transformations are then used to approximate integrals for maximum-likelihood update of subtomogram averages through expectation–maximization algorithm. Our tests on simulated and experimental subtomograms showed that, compared to our previously developed fast alignment method (FA), FAML is significantly more robust to noise and missing wedge effects with moderate increases of computation cost. Besides, FAML performs well with significantly fewer input subtomograms when the FA method fails. Therefore, FAML can serve as a key component for improved construction of initial structural models from macromolecules captured by CECT.Availability and implementation http://www.cs.cmu.edu/mxu1

A new memetic algorithm for multiple graph alignment

A new memetic algorithm for multiple graph alignment

Machine Vision-Based Positioning and Inspection Using Expectation–Maximization Technique

Precision positioning is very important for automatic assembly and inspection in the electronic manufacturing process. In this paper, we propose a fast image alignment method using the expectation–maximization (E–M) technique. The proposed algorithm is especially applied to positioning and defect inspection of printed circuit boards (PCBs). It can well handle deformed or incomplete object shapes with translation, rotation, and scale changes. The Canny edge detector is used to generate the edge maps of images. The E-step of the E–M procedure finds mutual edge points in both compared images by assigning weights to individual edge points. The mutual edge points give larger weights, while the foreign edge points in two images have smaller weights. The M-step then calculates the geometric transformation parameters using the weighted edge points in individual images. For an edge point in one image, a fast spiral search is proposed to find its corresponding edge point with the shortest distance in the other image. The spiral search is carried out by a predetermined lookup table, and no computation is involved in the search process. The weight of each edge point is inversely proportional to the neighboring distance. Experimental results indicate that the proposed E–M positioning method can achieve a translation error less than 1 pixel and a rotation error smaller than 1° for PCB positioning.

动车组列车序列图像快速对齐方法

动车组列车序列图像快速对齐方法

A fast read alignment method based on seed-and-vote for next generation sequencing.

BackgroundThe next-generation of sequencing technologies, along with the development of bioinformatics, are generating a growing number of reads every day. For the convenience of further research, these reads should be aligned to the reference genome by read alignment tools. Despite the diversity of read alignment tools, most have no comprehensive advantage in both accuracy and speed. For example, BWA has comparatively high accuracy, but its speed leaves much to be desired, becoming a bottleneck while an increasing number of reads need to be aligned every day. We believe that the speed of read alignment tools still has huge room for improvement, while maintaining little to no loss in accuracy.ResultsHere we implement a new read alignment tool, Fast Seed-and-Vote Aligner (FSVA), which is based on seeding and voting. FSVA achieves a high accuracy close to BWA and simultaneously has a very high speed. It only requires ~10–15 CPU hours to run a whole genome read alignment, which is ~5–7 times faster than BWA.ConclusionsIn some cases, reads have to be aligned in a short time. Where requirement of accuracy is not very stringent, FSVA would be a promising option.FSVA is available at https://github.com/Topwood91/FSVA

Dynamic initial coarse alignment of SINS for AUV using the velocity loci and pressure sensor

For the high-speed and light autonomous underwater vehicle (AUV), it is moving freely, and the speed and attitude are in dynamic movement. Then, the traditional static and quasi-static ground alignment cannot be used any more. Using the optimisation-based alignment (OBA) scheme, this study presents a novel estimation method for fast initial coarse alignment of a AUV's strapdown inertial navigation system (SINS). The novel OBA method use the inertial measurement unit, the pressure sensor measurements and the navigational velocity ν v in v-frame produced by the motor thrust to solve the attitude estimation problem which is known as Wahba's problem. Unlike several current techniques, the presented estimation method is effective to any movement form. The simulation results show that the attitude determined by this novel method can meet the accuracy requirement of coarse alignment and it can be used as input for the fine alignment.

Precise Control of Lamellar Thickness in Highly Oriented Regioregular Poly(3‐Hexylthiophene) Thin Films Prepared by High‐Temperature Rubbing: Correlations with Optical Properties and Charge Transport

Precise control of orientation and crystallinity is achieved in regioregular poly(3‐hexylthiophene) (P3HT) thin films by using high‐temperature rubbing, a fast and effective alignment method. Rubbing P3HT films at temperatures TR ≥ 144 °C generates highly oriented crystalline films with a periodic lamellar morphology with a dichroic ratio reaching 25. The crystallinity and the average crystal size along the chain axis direction, lc, are determined by high‐resolution transmission electron microscopy and differential scanning calorimetry. The inverse of the lamellar period l scales with the supercooling and can accordingly be controlled by the rubbing temperature TR. Uniquely, the observed exciton coupling in P3HT crystals is correlated to the length of the average planarized chain segments lc in the crystals. The high alignment and crystallinity observed for TR > 200 °C cannot translate to high hole mobilities parallel to the rubbing because of the adverse effect of amorphous zones interrupting charge transport between crystalline lamellae. Although tie chains bridge successive P3HT crystals through amorphous zones, their twisted conformation restrains interlamellar charge transport. The evolution of charge transport anisotropy is correlated to the evolution of the dominant contact plane from mainly face‐on (TR ≤ 100 °C) to edge‐on (TR ≥ 170 °C).

Genetic algorithm based fast alignment method for strap-down inertial navigation system with large azimuth misalignment.

In order to shorten the alignment time and eliminate the small initial misalignment limit for compass alignment of strap-down inertial navigation system (SINS), which is sometimes not easy to satisfy when the ship is moored or anchored, an optimal model based time-varying parameter compass alignment algorithm is proposed in this paper. The contributions of the work presented here are twofold. First, the optimization of compass alignment parameters, which involves a lot of trial-and-error traditionally, is achieved based on genetic algorithm. On this basis, second, the optimal parameter varying model is established by least-square polynomial fitting. Experiments are performed with a navigational grade fiber optical gyroscope SINS, which validate the efficiency of the proposed method.

Coarse alignment of a shipborne strapdown inertial navigation system using star sensor

This study presents a novel estimation method for fast initial coarse alignment of a shipborne strapdown inertial navigation system. Unlike several current techniques, the alignment accuracy of the presented estimation method is not reduced by the shipborne disturbances causing by wave action (when moored) and the inertial measurement unit output constant error. The coarse alignment method is based on the acceleration sensed by accelerometers and the attitude matrix respect to the inertial frame sensed by star sensor. The specific force along the inertial frame is derived from the acceleration sensed by accelerometers, and the information characteristics of the specific force along the inertial frame are discussed. The analysed results show that the constant and periodical information is included in the transformation specific force along the inertial frame. Therefore Butterworth low-pass filter is used to extract the constant information to calculate the attitude of the vehicle. The effectiveness of this approach was demonstrates by simulation and experimental study. The results showed this coarse alignment method can estimate attitude information, and the attitude errors of the alignment result are small angles. Therefore the alignment accuracy meets the demands of fine alignment.

Backtracking Integration for Fast Attitude Determination-Based Initial Alignment

By incorporating the backward navigation concept into the newly developed attitude determination-based initial alignment (ADIA) method, a fast initial alignment method is proposed. The contribution of the proposed method lies in the development of a backtracking integration procedure for the ADIA vector observations construction. With the special integration procedure for the vector observations construction, the acceleration information provided by the inertial measurement unit and aided global positioning system can be used more adequately with the proposed method, therefore resulting in a much improved performance. Field experiments demonstrate the validity of the proposed method.

A fast and high-accuracy transfer alignment method between M/S INS for ship based on iterative calculation

There are two viewpoints in the transfer alignment process given as follows: (1) the information used for matching in strapdown inertial navigation system (SINS) originates from the mathematical frame which cuts off the direct relationship between sensor measurement and misalignment angles; (2) in close correction mode, the estimated parameters from data fusion filter are used to participate in SINS navigation solution. Based on the above viewpoints, a novel transfer alignment method based on iterative calculation is designed, and in this method the alignment time is shortened and alignment accuracy is improved and the real-time property of alignment result is ensured with the following two methods: (1) during every data fusion period, sensor data and external reference navigation parameters are stored, and the backward and forward navigation solution and data fusion are executed once or several times with the help of high performance computer; (2) with the help of multi-tasking method, the operations for storing sensor data in the current fusion period, iterative calculation for the previous fusion period, and navigation solution for the current fusion period based on the stored data and real-time data are run in parallel but with different priorities. The simulation and turntable test under ship swinging condition indicate that alignment time of the proposed method is shortened compared with that of classical method when the data fusion times of two methods are equal; and alignment accuracy is improved when the alignment times are equal.

A fast compass alignment method for SINS based on saved data and repeated navigation solution

Compared with Gimbaled Inertial Navigation System (GINS), there are two differences in the compass alignment process for Strapdown INS (SINS) as follows: (1) the input signal is the projected sensor data from body frame to calculated navigation frame, not the sensor data; (2) the output control signal participates in navigation solution rather than driving navigation frame directly. Considering these characteristics, a fast compass alignment method based on iterative calculation is designed for SINS in this paper. With the help of high performance computer, the iterative process can be finished fast and the alignment time can be shortened obviously. However, there exist two problems in the new method, one of which is how to use the saved data, and the other is how to ensure the real-time property of alignment result. For the first problem, our simulation result shows that the forward–forward navigation solution method is more effective for compass alignment than the backward–forward one. And to solve the second problem, Multi-tasking method combined with Real Time Multi-tasking Operating System (RTOS) is used to trace the change of body frame and update the body frame of attitude matrix when the alignment is finished. The car test on a type of fiber-optic gyro SINS indicates that the alignment accuracy of the proposed method processed for 142s is as precise as that of the classical compass alignment method for 720s.

Automated target segmentation and real space fast alignment methods for high-throughput classification and averaging of crowded cryo-electron subtomograms

Motivation: Cryo-electron tomography allows the imaging of macromolecular complexes in near living conditions. To enhance the nominal resolution of a structure it is necessary to align and average individual subtomograms each containing identical complexes. However, if the sample of complexes is heterogeneous, it is necessary to first classify subtomograms into groups of identical complexes. This task becomes challenging when tomograms contain mixtures of unknown complexes extracted from a crowded environment. Two main challenges must be overcomed: First, classification of subtomograms must be performed without knowledge of template structures. However, most alignment methods are too slow to perform reference-free classification of a large number of (e.g. tens of thousands) of subtomograms. Second, subtomograms extracted from crowded cellular environments, contain often fragments of other structures besides the target complex. However, alignment methods generally assume that each subtomogram only contains one complex. Automatic methods are needed to identify the target complexes in a subtomogram even when its shape is unknown.Results: In this article, we propose an automatic and systematic method for the isolation and masking of target complexes in subtomograms extracted from crowded environments. Moreover, we also propose a fast alignment method using fast rotational matching in real space. Our experiments show that, compared with our previously proposed fast alignment method in reciprocal space, our new method significantly improves the alignment accuracy for highly distorted and especially crowded subtomograms. Such improvements are important for achieving successful and unbiased high-throughput reference-free structural classification of complexes inside whole-cell tomograms.Contact: alber@usc.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Large Scale Alignment and Charge Transport Anisotropy of pBTTT Films Oriented by High Temperature Rubbing

A large-scale alignment method is used to orient the conjugated polymer poly(2,5-bis(3-dodecyl-2-yl)thieno[3,2-b]thiophene) (C12-pBTTT). This fast one-step alignment method does not use any alignment layer and does not necessarily require postalignment annealing of the films. It exploits the increased plasticity of the conjugated polymer films for 50 °C ≤ T ≤ 125 °C to obtain high in-plane orientations by mechanical rubbing of the films. As visualized by HR-TEM, the in-plane alignment of C12-pBTTT chains and size of the oriented domains increase with the temperature of the film during rubbing (Tr). The domains have a preferential face-on orientation; i.e., the π-stacking direction is along the film normal and the chain direction parallel to the rubbing direction. Postrubbing annealing at T < 200 °C can further improve in-plane alignment whereas for T ≥ 200 °C, edge-on oriented C12-pBTTT crystals are formed. The anisotropy of hole transport for highly in-plane oriented face-on as well as edge-on oriented f...

A Fast and High-Accuracy Compass Alignment Method to SINS with Azimuth Axis Rotation

Azimuth axis rotating modulation was introduced to improve the alignment accuracy of strapdown inertial navigation system (SINS) through compass algorithm, in which the limit accuracy was determined by equivalent sensor errors in the eastern and northern direction. In this modulation, horizontal sensor errors were modulated into zero mean periodic variables. Furthermore, two methods were introduced to ensure alignment accuracy and speed: (1) shortened rotating cycle and redesigned compass parameters were selected to eliminate or ease the amplification to low-frequency senor error inputs in compass loop caused by rotation and (2) a data repeated calculation method was designed to shorten prolonged alignment time caused by the above redesigned parameters. Based on a certain SINS, turntable test proves that alignment accuracy and time were significantly improved and slightly shortened in comparison with the classical compass alignment.

Conservation of a Triple-Helix-Forming RNA Stability Element in Noncoding and Genomic RNAs of Diverse Viruses

Abundant expression of the long noncoding (lnc) PAN (polyadenylated nuclear) RNA by the human oncogenic gammaherpesvirus Kaposi's sarcoma-associated herpesvirus (KSHV) depends on a cis-element called the expression and nuclear retention element (ENE). The ENE upregulates PAN RNA by inhibiting its rapid nuclear decay through triple-helix formation with the poly(A) tail. Using structure-based bioinformatics, we identified six ENE-like elements in evolutionarily diverse viral genomes. Five are in double-stranded DNA viruses, including mammalian herpesviruses, insect polydnaviruses, and a protist mimivirus. One is in an insect picorna-like positive-strand RNA virus, suggesting that the ENE can counteract cytoplasmic as well as nuclear RNA decay pathways. Functionality of four of the ENEs was demonstrated by increased accumulation of an intronless polyadenylated reporter transcript in human cells. Identification of these ENEs enabled the discovery of PAN RNA homologs in two additional gammaherpesviruses, RRV and EHV2. Our findings demonstrate that searching for structural elements can lead to rapid identification of lncRNAs.

High-throughput subtomogram alignment and classification by Fourier space constrained fast volumetric matching

Cryo-electron tomography allows the visualization of macromolecular complexes in their cellular environments in close-to-live conditions. The nominal resolution of subtomograms can be significantly increased when individual subtomograms of the same kind are aligned and averaged. A vital step for such a procedure are algorithms that speedup subtomogram alignment and improve its accuracy to allow reference-free subtomogram classifications. Such methods will facilitate automation of tomography analysis and overall high throughput in the data processing. Building on previous work, here we propose a fast rotational alignment method that uses the Fourier equivalent form of a popular constrained correlation measure that considers missing wedge corrections and density variances in the subtomograms. The fast rotational search is based on 3D volumetric matching, which improves the rotational alignment accuracy in particular for highly distorted subtomograms with low SNR and tilt angle ranges in comparison to fast rotational matching of projected 2D spherical images. We further integrate our fast rotational alignment method in a reference-free iterative subtomogram classification scheme, and propose a local feature enhancement strategy in the classification process. As a proof of principle, we can demonstrate that the automatic method can successfully classify a large number of experimental subtomograms without the need of a reference structure.

Calibration and Initial Alignment of Low Cost MEMS Inertial Navigation Sensors for UAV Application

This work deals with an simple approach to calibrate low cost six degree of freedom MEMS inertial Navigation system to be used in Unmanned Air Vehicle (UAV). The accelerometer and gyroscope are modelled with inter axis misalignment correction. To determine calibration parameters of a tri axis accelerometer at least nine equations will be required to solve for nine unknowns (3 scale factor, 3 zero bias, 3 misalignment angles). In this simple approach three new linear equations were formulated to determine the calibration parameters thereby reducing number of positions needed in multi position test. The formulated methodology for accelerometer is validated by conducting twelve position tests. All combination of positions were attempted iteratively. After identifying the singularities, the study on the results suggests that only six positions are enough to solve nine unknowns. Similar methodology was applied to calibrate tri axial Gyroscope in rate test. Rate test results were studied and analysed with standard values provided my sensor manufacturer. A strap down inertial navigation system (SINS) error model is introduced, and the observability of the SINS error model is analyzed. Then on the basis of this SINS error model and a kalman filter is used to estimate the states of the error models. Based on the analysis of computer simulation results, a fast and precision initial alignment method is proposed for SINS on stationary base.

Coarse Alignment of a Ship's Strapdown Inertial Attitude Reference System Using Velocity Loci

This paper presents a novel estimation method for fast initial coarse alignment of a ship's strapdown inertial attitude reference system using only inertial measurement unit (IMU) measurements for quasi-static alignment and IMU measurements with GPS aiding for moving-base alignment. Unlike several current techniques, the presented estimation method is effective with any initial attitude error. The estimator is based on the decomposition of the attitude quaternion into separate Earth motion, inertial rate, and alignment quaternions. The alignment quaternion is estimated using a minimum variance fit between loci of body- and navigation-frame velocity vectors using solutions to Wahba's problem. One set of vectors is derived from time integrals of measured vehicle motions, and the second set is derived from Earth motion and GPS data (when moving). For the case of quasi-static alignment, an algebraic expression for the covariance of the attitude estimate as a function of the variance of navigation-frame velocity disturbances is developed. It is shown that, by averaging and interleaving the velocity vectors, the resulting attitude estimate is improved over sequential sampling techniques. It is further shown, for a maneuvering vessel, that a continuous estimate of the attitude error covariance can be generated from the IMU data. This latter feature allows direct initialization of a follow-on fine-alignment stochastic estimator's covariance matrix. Results are presented for quasi-static alignment using inertial sensors only and for full in-motion alignment using navigation-frame GPS velocity and position aiding.

Robust 3D Face Recognition by Local Shape Difference Boosting

This paper proposes a new 3D face recognition approach, Collective Shape Difference Classifier (CSDC), to meet practical application requirements, i.e., high recognition performance, high computational efficiency, and easy implementation. We first present a fast posture alignment method which is self-dependent and avoids the registration between an input face against every face in the gallery. Then, a Signed Shape Difference Map (SSDM) is computed between two aligned 3D faces as a mediate representation for the shape comparison. Based on the SSDMs, three kinds of features are used to encode both the local similarity and the change characteristics between facial shapes. The most discriminative local features are selected optimally by boosting and trained as weak classifiers for assembling three collective strong classifiers, namely, CSDCs with respect to the three kinds of features. Different schemes are designed for verification and identification to pursue high performance in both recognition and computation. The experiments, carried out on FRGC v2 with the standard protocol, yield three verification rates all better than 97.9 percent with the FAR of 0.1 percent and rank-1 recognition rates above 98 percent. Each recognition against a gallery with 1,000 faces only takes about 3.6 seconds. These experimental results demonstrate that our algorithm is not only effective but also time efficient.