Improve Alignment Accuracy Research Articles

An Alignment Method Based on KF-ASMUKF Hybrid Filtering for Ship's SINS under Mooring Conditions.

To solve the problem that the ship’s strapdown inertial navigation system (SINS) alignment accuracy decreases with the increase of the nonlinear filtering state dimension under mooring conditions, a method based on Kalman filter (KF) and Adaptive scale mini-skewness single line sampling Unscented Kalman Filter (ASMUKF) hybrid filtering algorithm is proposed in this paper. Three improvements are made as the following: (1) adopt a new sampling strategy. To obtain the ASMUKF filtering algorithm, scale mini-skewness single line sampling is used to replaced the traditional symmetrical sampling method and an adaptive scale factor is adapted into the Unscented Kalman Filter (UKF) to correct the real-time transformation sampling process; (2) the improved ASMUKF algorithm is combined with KF to form KF-ASMUKF hybrid filtering model; (3) the hybrid filtering model is divided into linear and nonlinear parts. The linear filtering part adopts the KF filtering model and the nonlinear filtering part adopts the ASMUKF model. Then, the calculation steps of the hybrid filtering algorithm is designed in this paper. The simulation and experimental results show that the hybrid filtering algorithm proposed has certain advantages over the traditional algorithm, and it can reduce the ship’s SINS calculation amount and improve alignment accuracy under mooring conditions.

Fuzzy entity alignment via knowledge embedding with awareness of uncertainty measure

Entity alignment refers to associate entities in different knowledge graphs if they are semantically identical. Embedding-based entity alignment approaches encode entities in a continuous embedding space where entities are aligned based on the similarity of learned embeddings. However, there exists ambiguity and uncertainty in entity alignment caused by single alignment metric. In this paper, a fuzzy entity alignment method FuzzyEA is proposed to model the uncertainty in alignment process based on intuitionistic fuzzy set (IFS). Iterative TransE model is designed to learn relational structure of knowledge graphs, where mutual selection and error correction mechanism is proposed to enhance the effect of iteration. The alignment results obtained by name/description embedding and structure embedding are fused based on Dempster’s combination rule. Experiments on three benchmark datasets demonstrate that the proposed FuzzyEA consistently outperforms other entity alignment methods and contributes to promising improvement in alignment accuracy and discrimination ability.

Targeting repeatability of a less obtrusive surgical navigation procedure for total shoulder arthroplasty.

Surgical navigation systems have demonstrated improvements in alignment accuracy in a number of arthroplasty procedures, but they have not yet been widely adopted for use in total shoulder arthroplasty (TSA). We believe this is due in part to the obtrusiveness of conventional optical tracking systems, as well as the need for additional intraoperative steps such as calibration and registration. The purpose of this study is to evaluate the feasibility of adapting a less-intrusive dental navigation system for use in TSA. We developed a proof-of-concept system based on validated laser-engraved surgical tools recently introduced for use in dental surgery that are calibrated once when manufactured and not recalibrated at time of use. The design also features a notably smaller bone-mounted tracker that can be tracked from a wide range of viewing angles. To assess our system's performance, we modified the dental surgical software to support guidance of a TSA procedure. We then conducted a user study in which three participants with varying surgical experience used the system to drill 30 holes in a glenoid model. Using a coordinate measuring machine, we determined the resulting drilled trajectory and compared this to the pre-planned trajectory. Since we used a model glenoid rather than anatomical specimens, we report on targeting precision rather than overall procedure precision or accuracy. We found targeting precision < 1mm (standard deviation) for locating the entry hole and < ~ 1° (SD) for both version and inclination. The latter value was markedly lower than the end-to-end angular precision achieved by previously reported TSA navigation systems (approximately 3°-5° SD). We conclude that variability during the targeting phase represents a small fraction of the overall variability exhibited by existing systems, so a less obtrusive navigation system for TSA based on laser-engraved tooling is likely feasible, which could improve the uptake rates of surgical navigation for TSA, thereby potentially leading to improved overall surgical outcomes.

Robotics improves alignment accuracy and reduces early revision rates for UKA in the hands of low-volume UKA surgeons

PurposeIt is known that in uni-compartmental knee arthroplasty (UKA) low-volume surgeons have a higher complication and revision rate than high-volume surgeons. Further, robotic-assisted UKA leads to lower early revision rate as well as fewer limb and joint line outliers compared to conventional UKA. The purpose of this study was to retrospectively analyze the outliers’ and revision rate of low-volume UKA surgeons with different robotic systems at short-term follow-up.MethodsIn this case–control study, 103 robotic-assisted UKAs were included. The procedures were performed between 2016 and 2019 from two low-volume UKA surgeons with an imageless (IL) (63 patients) and image-based (IB) (40 patients) robotic system. Alignment outliers, joint line (JL) reconstruction, complication and revision rates of the two different robotic systems were analyzed. The minimum follow-up was two years. Outliers were defined as a postoperative valgus malalignment greater than 182°. The surgery time for all procedures was evaluated.ResultsThe overall revision rate was 3.9% (4 of 103). Two occurred in the IB group (5.0%) and two in the IL group (3.2%). No valgus malalignment outliers were observed in both groups. The mean JL was not distalized by more than 2 mm in both groups (IL: 1.3 ± 1.6 mm vs. IB: 1.8 ± 0.9 mm, p value 0.08). The IL procedures had a significant lower mean surgery time (55 ± 13 min vs. 68 ± 14, p value 0.001).ConclusionRobotic-assisted UKA is a safe procedure in the hand of low-volume UKA surgeons. Robotic-assisted UKA minimizes overcorrection into valgus mal-alignment. Low revision rates are observed at short-term follow-up for robotic-assisted UKA. The choice of the different robotic systems has no impact on the outcome.

Methods to achieve fast, accurate, and mechanically robust optical breadboard alignment

Typical laboratory optical systems use commercially off-the-shelf components in which emphasis is oriented toward ease of assembly and a wide range of adjustability. However, these mounts often require individual alignments that, when each degree of adjustability is cumulated in a complex optical system, can be inefficient and time consuming. Furthermore, most of these optomechanical mounts lack the mechanical robustness required to maintain operational performances out of the laboratory environment. An optomechanical assembly method based on passively aligning design features is proposed to simplify breadboard level optical systems, to improve alignment accuracy and maintaining operational pointing stability. Given the recent improvements in lens passive centering techniques, it seemed worth exploring methods to reduce alignment time and improve the mechanical robustness of laboratory setups. Recent studies show that a typical optical lens centering of <1 arc min with respect to its mount can be achieved using patented auto centering and edge contact mounting technologies. To achieve similar position accuracy between multiple lenses on a portable breadboard, lens mounts should be designed and built with proper reference surfaces and a system should easily reference one mount with respect to the other. The use of reference spheres and dedicated optomechanical mounts is employed to leverage the standard threaded holes of laboratory breadboards and achieve precise lens mount positioning. A series of optomechanical mounts incorporating these techniques are therefore tested. Position accuracy and repeatability are measured mechanically with a coordinate measuring machine and optically with the active monitoring of a laser beam centroid position. Measured position accuracy at the optomechanical mount level is <50 μm with a repeatability of less than 5 μm per interface. The optomechanical mounts robustness is tested within typical storage temperature range of −46 ° C to 63°C and at vibrations levels exceeding typical shipping conditions. Measured optical pointing stability of a simple optical system after environmental testing was found to be under 25 μm. This method should be a promising solution to bridge the design technological gap between the early prototyping and the production phases.

Point cloud registration algorithm based on curvature feature similarity

In this paper, an improved iterative closest point (ICP) algorithm based on the curvature feature similarity of the point cloud is proposed to improve the performance of classic ICP algorithm in an unstructured environment, such as alignment accuracy, robustness and stability. A K-D tree is introduced to segment the 3D point cloud for speeding up the search of nearest neighbor points using principal component analysis for coarse alignment based on the classical ICP algorithm. In the curvature calculation process, discrete index mapping and templates are taken for sampling to simplify the point cloud data and improve the registration efficiency. The nearest point of Euclidean distance is searched based on curvature feature similarity to improve alignment accuracy. The results of the point cloud alignment experiments show that the response time of the algorithm is less than 5s in the case where the curvature features of point cloud are obvious. And the alignment error can be reduced to 1% of the pre-alignment error. Therefore, the algorithm is an efficient, accurate and practical option for unstructured environment applications.

Research on initial alignment method of vehicle-mounted SINS based on reverse navigation

In order to improve the alignment accuracy and speed of vehicle-mounted SINS, an initial alignment scheme of “inertial solidification alignment + Kalman filter fine alignment based on reverse navigation” is proposed in this paper. Firstly, an inertial solidification alignment algorithm is derived, the initial alignment problem is transformed into Wahba problem, and the optimal attitude matrix at the initial moment is obtained by singular value decomposition algorithm. The inertial solidification alignment algorithm is more concise and intuitive than the traditional alignment algorithm of geocentric inertial coordinate system. Then, we analyzed the effectiveness of rotation modulation technology to improve alignment accuracy theoretically and proved it by simulation. And it is pointed out that the application platform space is limited and the system cost is increased when using this technology. Furthermore, in order to overcome the shortcomings of using rotation modulation technology, a Kalman filter algorithm based on reverse navigation is derived. By reusing the data stored during the inertial solidification alignment, the alignment time is extended equivalently, the initial attitude error is reduced and the attitude calculation accuracy after forward navigation is improved, higher precision alignment is realized. Finally, the effectiveness of the initial alignment scheme is verified by simulation.

Reference flow: reducing reference bias using multiple population genomes

Most sequencing data analyses start by aligning sequencing reads to a linear reference genome, but failure to account for genetic variation leads to reference bias and confounding of results downstream. Other approaches replace the linear reference with structures like graphs that can include genetic variation, incurring major computational overhead. We propose the reference flow alignment method that uses multiple population reference genomes to improve alignment accuracy and reduce reference bias. Compared to the graph aligner vg, reference flow achieves a similar level of accuracy and bias avoidance but with 14% of the memory footprint and 5.5 times the speed.

A Postprocessing-Technique-Based Switching Loss Estimation Method for GaN Devices

Gallium nitride (GaN) high electron mobility transistor (HEMT) is a promising candidate for the high-density power converter applications. Due to the low switching loss, the GaN HEMT may lead to a new horizon in the applications, such as fast charger, wireless charging, and 5G power amplifier. However, the fast switching speed of GaN HEMT makes it extremely sensitive to parasitic parameters, especially for the low-voltage GaN devices with small packages. Conventional switching loss estimation methods, which are normally based on the calibration fixture or modification of test circuit, cannot be effectively utilized for GaN HEMT. This article presents an accurate switching loss estimation method using the postprocessing technique. The proposed switching loss technique consists of three parts of signal processing, which are the wavelet denoising process to minimize the influence of background noise, the voltage–current ( $ V-I$ ) alignment process to reduce errors from probe propagation delay, and the linear interpolation process for further improvement of alignment accuracy. In addition, a modified SPICE model is proposed to investigate the influence of parasitic parameters on switching losses by the circuit simulation. Based on the theoretical switching characteristics, the switching loss estimation method is finally validated experimentally on a commercial 40-V/10-A GaN HEMT in a double-pulse test.

Accelerometer-Based, Computer-Navigated Total Knee Arthroplasty to Correct a Complex Deformity in a Patient With Multiple Hereditary Exostoses

BackgroundAccelerometer-based computer-assisted navigation systems (ABCANSs) have been shown to improve alignment accuracy in total knee arthroplasty (TKA) and are effective in treating complex extra-articular deformity. We present an ABCANS-assisted TKA performed in a 68-year-old male with end-stage arthritis of the right knee, in the setting of a severe valgus deformity secondary to multiple hereditary exostoses. MethodsThe KneeAlign 2 system (OrthAlign, Inc.; Aliso Viejo, CA) was used to perform the TKA in this clinical scenario, given its functionality, which allows angular correction to be tailored to a given deformity, and its reported accuracy in performance of bony resection in TKA. The patient was prospectively followed up for one year postoperatively. Radiographs, PROMs, and patient satisfaction were reported. ResultsAfter the ABCANS-assisted TKA, the patient's alignment was improved from 25° to 4° of valgus. His final range of motion was 0-135° without an instability. In addition, the patient reported excellent scores on multiple joint-specific outcome measures, including the Knee Injury and Osteoarthritis Outcome Score for Joint Replacement, the Forgotten Joint Score, and the Oxford Knee Score. ConclusionThis case report illustrates the rationale, technique, and the excellent clinical outcomes achieved in a complex patient with extra-articular deformity using an ABCANS-assisted TKA.

CLEAR: A Consistent Lifting, Embedding, and Alignment Rectification Algorithm for Multiview Data Association

Many robotics applications require alignment and fusion of observations obtained at multiple views to form a global model of the environment. Multiway data association methods provide a mechanism to improve alignment accuracy of pairwise associations and ensure their consistency. However, existing methods that solve this computationally challenging problem are often too slow for real-time applications. Furthermore, some of the existing techniques can violate the cycle consistency principle, thus drastically reducing the fusion accuracy. This article presents the consistent lifting, embedding, and alignment rectification (CLEAR) algorithm to address these issues. By leveraging insights from the multiway matching and spectral graph clustering literature, CLEAR provides cycle-consistent and accurate solutions in a computationally efficient manner. Numerical experiments on both synthetic and real datasets are carried out to demonstrate the scalability and superior performance of our algorithm in real-world problems. This algorithmic framework can provide significant improvement in the accuracy and efficiency of existing discrete assignment problems, which traditionally use pairwise (but potentially inconsistent) correspondences. An implementation of CLEAR is made publicly available online.

Supermatrix phylogeny resolves goby lineages and reveals unstable root of Gobiaria

Gobies, sleepers, and cardinalfishes represent major clades of a species rich radiation of small bodied, ecologically diverse percomorphs (Gobiaria). Molecular phylogenetics has been crucial to resolving broad relationships of sleepers and gobies (Gobioidei), but the phylogenetic placements of cardinalfishes and nurseryfishes, as reciprocal or sequential sister clades to Gobioidei, are uncertain. In order to evaluate relationships among and within families we used a phylogenetic data mining approach to generate densely sampled trees inclusive of all higher taxa. We utilized conspecific amino acid homology to improve alignment accuracy, included ambiguously identified taxa to increase taxon sampling density, and resampled individual gene alignments to filter rogue sequences before concatenation. This approach yielded the most comprehensive tree yet of Gobiaria, inferred from a sparse (17 percent-complete) supermatrix of one ribosomal and 22 protein coding loci (18,065 characters), comprised of 50 outgroup and 777 ingroup taxa, representing 32 percent of species and 68 percent of genera. Our analyses confirmed the lineage-based classification of gobies with strong support, identified sleeper clades with unforeseen levels of systematic uncertainty, and quantified competing phylogenetic signals that confound resolution of the root topology. We also discovered that multilocus data completeness was related to maximum likelihood branch support, and verified that the phylogenetic uncertainty of shallow relationships observed within goby lineages could largely be explained by supermatrix sparseness. These results demonstrate the potential and limits of publicly available sequence data for producing densely-sampled phylogenetic trees of exceptionally biodiverse groups.

An Alignment Method for Strapdown Inertial Navigation Systems Assisted by Doppler Radar on a Vehicle-Borne Moving Base.

In this study, we investigated a novel method for high-accuracy autonomous alignment of a strapdown inertial navigation system assisted by Doppler radar on a vehicle-borne moving base, which effectively avoids the measurement errors caused by wheel-slip or vehicle-sliding. Using the gyroscopes in a strapdown inertial navigation system and Doppler radar, we calculated the dead reckoning, analyzed the error sources of the dead reckoning system, and established an error model. Then the errors of the strapdown inertial navigation system and dead reckoning system were treated as the states. Besides velocity information, attitude information was cleverly introduced into the alignment measurement to improve alignment accuracy and reduce alignment time. Therefore, the first measurement was the difference between the output attitude and velocity of the strapdown inertial navigation system and the corresponding signals from the dead reckoning system. In order to further improve the alignment accuracy, more measurement information was introduced by using the vehicle motion constraint, that is, the velocity output projection of strapdown inertial navigation system along the transverse and vertical direction of the vehicle body was also used as the second measurement. Then the corresponding state and measurement equations were established, and the Kalman filter algorithm was used for assisted alignment filtering. The simulation results showed that, with a moving base, the misalignment angle estimation accuracy was better than 0.5’ in the east direction, 0.4’ in the north direction, and 3.2’ in the vertical direction.

NUMT Confounding Biases Mitochondrial Heteroplasmy Calls in Favor of the Reference Allele.

Homology between mitochondrial DNA (mtDNA) and nuclear DNA of mitochondrial origin (nuMTs) causes confounding when aligning short sequence reads to the reference human genome, as the true sequence origin cannot be determined. Using a systematic in silico approach, we here report the impact of all potential mitochondrial variants on alignment accuracy and variant calling. A total of 49,707 possible mutations were introduced across the 16,569 bp reference mitochondrial genome (16,569 × 3 alternative alleles), one variant at-at-time. The resulting in silico fragmentation and alignment to the entire reference genome (GRCh38) revealed preferential mapping of mutated mitochondrial fragments to nuclear loci, as variants increased loci similarity to nuMTs, for a total of 807, 362, and 41 variants at 333, 144, and 27 positions when using 100, 150, and 300 bp single-end fragments. We subsequently modeled these affected variants at 50% heteroplasmy and carried out variant calling, observing bias in the reported allele frequencies in favor of the reference allele. Four variants (chrM:6023A, chrM:4456T, chrM:5147A, and chrM:7521A) including a possible hypertension factor, chrM:4456T, caused 100% loss of coverage at the mutated position (with all 100 bp single-end fragments aligning to homologous, nuclear positions instead of chrM), rendering these variants undetectable when aligning to the entire reference genome. Furthermore, four mitochondrial variants reported to be pathogenic were found to cause significant loss of coverage and select haplogroup-defining SNPs were shown to exacerbate the loss of coverage caused by surrounding variants. Increased fragment length and use of paired-end reads both improved alignment accuracy.

Shape-optimizing mesh warping method for stereoscopic panorama stitching

In this paper, we propose a novel shape-optimizing mesh warping method for stereoscopic panorama stitching, which aims to resolve shape distortion and unnatural rotation of traditional stitching methods, simultaneously coping with the challenges, misalignment, and stereoscopic inconsistency. Specifically, based on the grid mesh analysis of projective warping, we propose a differential warping method by gradually changing the inclination angle of each mesh line in non-overlapping regions of the image to reduce shape distortion and unnatural rotation. Furthermore, an extended moving direct linear transformation method is proposed to effectively and robustly improve alignment accuracy and maintain stereoscopic consistency in multiple stereoscopic images. Finally, a consistent seam based on the matched feature points in the left- and right- view images of a stereoscopic image is designed to blend images and generate a stereoscopic panorama image. Experiments demonstrate that the proposed method has a superior performance compared to previous methods.

A joint method for marker-free alignment of tilt series in electron tomography.

MotivationElectron tomography (ET) is a widely used technology for 3D macro-molecular structure reconstruction. To obtain a satisfiable tomogram reconstruction, several key processes are involved, one of which is the calibration of projection parameters of the tilt series. Although fiducial marker-based alignment for tilt series has been well studied, marker-free alignment remains a challenge, which requires identifying and tracking the identical objects (landmarks) through different projections. However, the tracking of these landmarks is usually affected by the pixel density (intensity) change caused by the geometry difference in different views. The tracked landmarks will be used to determine the projection parameters. Meanwhile, different projection parameters will also affect the localization of landmarks. Currently, there is no alignment method that takes interrelationship between the projection parameters and the landmarks.ResultsHere, we propose a novel, joint method for marker-free alignment of tilt series in ET, by utilizing the information underlying the interrelationship between the projection model and the landmarks. The proposed method is the first joint solution that combines the extrinsic (track-based) alignment and the intrinsic (intensity-based) alignment, in which the localization of landmarks and projection parameters keep refining each other until convergence. This iterative approach makes our solution robust to different initial parameters and extreme geometric changes, which ensures a better reconstruction for marker-free ET. Comprehensive experimental results on three real datasets show that our new method achieved a significant improvement in alignment accuracy and reconstruction quality, compared to the state-of-the-art methods.Availability and implementationThe main program is available at https://github.com/icthrm/joint-marker-free-alignment.Supplementary information Supplementary data are available at Bioinformatics online.

Fast and Efficient Parallel Alignment Model for Aligning both Long and Short Sentences

Recently, demand for fast and efficient translation system been widely seen. However, translation model are dependent parallel corpora. However, it is challenging to obtain large parallel corpora for resource starved language such as Kannada-Telugu pair. The existing Giza++ based word alignment and Moses phrase based alignment model are efficient for aligning only short sentences. However, for longer sentence the accuracy of model degrades. For performing alignment for longer sentences, neural based alignment has been presented in recent times. However, these models are trained using fixed vector length. Thus, induces memory and training overhead. For overcoming research challenges, this work presents a parallel alignment model using recurrent neural network (RNN). Further, to utilize memory efficiently and minimize training time parallel execution of RNN under GPU is considered. For improving alignment accuracy presented a cost function by combing statistical and neural based alignment method. Experiment are conducted to evaluate the proposed alignment model in terms of accuracy, Word alignment error (WAE), memory utilization, and computation time.

Trajectory planning method for improving alignment accuracy of probes for dual-robot air-coupled ultrasonic testing system

Composite workpieces, especially the complex-curved surfaces composite workpieces, have been increasingly used in different industries. Non-destructive testing of these parts has become an urgent problem to be addressed. To solve the problem, this article presents a dual-robot air-coupled ultrasonic non-destructive testing scheme and introduces the structure of the system and a general calibration method for the workpiece frame of a dual-robot system in detail. Importantly, this article proposes a tangential constraint method, which makes the probes completely aligned during the inspection process. Verification experiments and ultrasonic testing experiments for a glued multilayered composite workpiece were performed using the dual-robot air-coupled ultrasonic non-destructive testing system. A comparative experiment was also performed using a dual-robot water jet-coupling ultrasonic testing system. Experimental results show that the dual-robot non-destructive testing scheme and the tangential constraint method function well, and all the artificial defects on the sample can be detected by both kinds of testing methods. Vivid 3-D C-scan image based on the test result is provided for convenience of observation. In other words, a kind of flexible versatile testing platform with multiple degrees of freedom is established.

OPTIMIR, a novel algorithm for integrating available genome-wide genotype data into miRNA sequence alignment analysis.

Next-generation sequencing is an increasingly popular and efficient approach to characterize the full set of microRNAs (miRNAs) present in human biosamples. MiRNAs’ detection and quantification still remain a challenge as they can undergo different posttranscriptional modifications and might harbor genetic variations (polymiRs) that may impact on the alignment step. We present a novel algorithm, OPTIMIR, that incorporates biological knowledge on miRNA editing and genome-wide genotype data available in the processed samples to improve alignment accuracy. OPTIMIR was applied to 391 human plasma samples that had been typed with genome-wide genotyping arrays. OPTIMIR was able to detect genotyping errors, suggested the existence of novel miRNAs and highlighted the allelic imbalance expression of polymiRs in heterozygous carriers. OPTIMIR is written in python, and freely available on the GENMED website (http://www.genmed.fr/index.php/fr/) and on Github (github.com/FlorianThibord/OptimiR).

Alignment mark optimization for improving signal-to-noise ratio of wafer alignment signal.

Phase diffraction gratings are widely used as alignment marks in wafer alignment systems. A higher alignment accuracy can be obtained by using higher diffraction orders of the alignment mark. Meanwhile, the alignment accuracy is also affected by the signal-to-noise ratio (SNR) of the alignment signal. The diffraction efficiency of the alignment mark is significantly reduced in the practical lithography process because of the strong absorption of the opaque film stacks on the mark surface, especially the metal layer. The reduction of the diffraction efficiency leads to a deterioration of the SNR of the alignment signal. An equal subsegmented phase grating is usually used to improve the diffraction efficiency of higher odd orders, so as to improve the SNR of the corresponding alignment signal. However, there is still a relatively high diffraction efficiency of the zeroth and even orders of such a grating. They will affect the SNR of the alignment signal of odd diffraction orders, which are usually used to measure mark position. In this paper, we propose a method to improve the diffraction efficiency of odd orders for a subsegmented phase grating through optimizing the structure of the alignment mark. Moreover, the diffraction efficiency of the zeroth and even orders, which are not used in the measurement process of mark position, are sufficiently reduced. Simulation results indicate that the SNR of the alignment signal was obviously improved by the proposed method, which is very helpful for improving alignment accuracy.