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In this paper, a self-alignment method for strapdown inertial navigation systems based on the q-method is studied. In addition, an improved method based on integrating gravitational apparent motion to form apparent velocity is designed, which can reduce the random noises of the observation vectors. For further analysis, a novel self-alignment method using a Kalman filter based on adaptive filter technology is proposed, which transforms the self-alignment procedure into an attitude estimation using the observation vectors. In the proposed method, a linear psuedo-measurement equation is adopted by employing the transfer method between the quaternion and the observation vectors. Analysis and simulation indicate that the accuracy of the self-alignment is improved. Meanwhile, to improve the convergence rate of the proposed method, a new method based on parameter recognition and a reconstruction algorithm for apparent gravitation is devised, which can reduce the influence of the random noises of the observation vectors. Simulations and turntable tests are carried out, and the results indicate that the proposed method can acquire sound alignment results with lower standard variances, and can obtain higher alignment accuracy and a faster convergence rate.

This paper demonstrates that “completely-jigless” assembly of a model product that requires fitting accuracy at the level of industrial products is possible by using a universal hand with four parallel stick fingers mounted on a conventional position-control-based industrial robot. Assuming that each part is taken out of the parts bin and temporarily placed on the work table, the accuracy required for precise fitting cannot be achieved with a vision sensor alone. Introducing an appropriate grasping strategy, the initial position error of the part is absorbed by self-alignment in the process of grasping. Once the alignment is completed, the pose of the grasped part is fixed and jigless assembly is possible with a conventional industrial robot, which has high repeatability. In this paper, we use a gear unit as an example of an industrial product and present some grasping strategies with the universal hand. We also propose some subsequent assembly strategies for shafts and gears. Using those grasping and assembly strategies, it is shown that jigless assembly of the gear unit was successfully completed in the experiment. Although the target product in this paper is specific, the assembly elements in this product, such as shaft screwing, bearing insertion, and gear meshing, are also included in many other products. Therefore, the methods shown in this paper can be applied to other products.

Carbon nanotubes (CNTs), owing to their superior electrical and mechanical properties, are a promising alternative to nonmetallic electrically conducting materials. In practice, cellulose as a low‐cost sustainable matrix has been used to prepare the aqueous dispersion of cellulose‐CNT (C‐CNT) nanocomposites. However, the compatibility with conventional solution‐processing and structural rearrangement for improving conductivity has yet to be determined. Herein, a straightforward route to prepare a conductive composite material from single‐walled CNTs (SWCNTs) and natural pulp is reported. High‐power shaking realizes the self‐alignment of individual SWCNTs in a cellulose matrix, resulting from the structural change in molecular orientations owing to countless collisions of zirconia beads in the aqueous mixture. The structural analysis of the dried C‐CNT films confirms that the entanglement and dispersion of C‐CNT nanowires determine the mechanical and electrical properties. Moreover, the rheological behavior of C‐CNT inks explains their coating and printing characteristics. By controlling shaking time, the electrical conductivity of the C‐CNT films with only 9 wt.% of SWCNTs from 0.9 to 102.4 S cm−1 are adjusted. the optimized C‐CNT ink is highly compatible with the conventional coating and printing processes on diverse substrates, thus finding potential applications in eco‐friendly, highly flexible, and stretchable electrodes is also demonstrated. This paper presents a novel and straightforward route to prepare an eco‐friendly nonmetallic conducting ink using natural cellulose and SWCNTs. The self‐alignment of individual SWCNTs in a cellulose matrix, resulting from the structural change in molecular orientations, realizes a highly conductive nanocomposite. The prepared nanocomposite ink is highly compatible with the conventional coating and printing processes on diverse substrates.

Purpose There are three major processes in the surface mounting technology (SMT) manufacturing line, namely, printing, mounting and reflowing. During the reflow process, the printed solder pastes are melted into liquid and cooled down into solid again, forming the solder joint. During this process, because of the combined force of the liquid solder, the components will move from the placed location to the final location. This is known as the self-alignment performance in the reflow process. From the comparable studies, it is known that the reflow process with a longer time above the liquidus (TAL) results in better self-alignment performance, as well as higher peak temperatures of the reflow profiles. The TAL and the peak temperatures are influenced by multiple factors, but the experimental designs from the comparable studies kept the same ramping and cooling slopes to modify the TAL and the peak temperature. The purpose of this study is to study on the multiple factors influencing the TAL and the peak temperatures (ramping slope, cooling slope and peak temperature) by conducting designed experiments for each of the factors. Design/methodology/approach In this study, the TAL-influencing features are studied independently, including ramping slope, cooling slope and peak temperature; designed and conducted an experiment to reveal the relationship between the self-alignment and each of the three features; the statistical-based model for the combination of the three features for optimal self-alignment performance; and proposed a statistical-based simulation model for the offset after reflow. Findings The authors conducted a case study validating the mounter optimization model previously proposed. As a result, the optimized reflow profile improved the self-alignment performance by at least 10%, and the simulation within the error of 15 µm. Research limitations/implications This research is statistical-based, which is limited to component types and sizes used in the design of experiments (DOE). The model proposed in this study can suggest a new reflow profile that can increase the self-alignment performance, which is critical to the solder joint quality, especially long-term quality. Practical implications This study can suggest a new reflow profile that can increase the self-alignment performance, which is critical to the solder joint quality, especially long-term quality. Social implications This study can suggest a new reflow profile that can increase the self-alignment performance, which is critical to the solder joint quality, especially long-term quality. Originality/value The proposed statistical-based soldering reflow target profile optimization model offers a novel and practical approach. The soldering profile provided by the manufacturer contains recommended and acceptable ranges in the critical features. This study provides the optimal setting within the ranges.

A new concept for SiC MOSFET with a self-aligned channel is presented. The channel is defined by shallow source-JFET implantation into a counter-doped layer. This concept is verified by TCAD device simulations. It is shown that the method is applicable to fabrication of functional devices. The most critical parameter of the process is misalignment between channel and p-shield. Almost no change of electrical current in forward conduction state and the leakage current and electric field in the gate oxide in blocking state is observed for the misalignments below 400 nm.

We report on self-aligned Ti TES single-photon detectors embedded in a 1550 nm optical cavity. The circular TES chip is shaped with a dry-etch process from the backside to protect the TES and wiring from possible damage and aligned to a single-mode fiber using a standard fiber ferrule and a matching sleeve. The critical temperature of Ti film is about 300 mK, resulting in a relatively short time constant of 1.3 μs. By choosing an active area of 15 × 15 μm 2 , our optical Ti TES can distinguish single photons at 1550 nm and reaches a system photon detection efficiency of 55% and an energy resolution of about 0.7 eV.

We have developed a manufacturing process for micromirrors based on microelectromechanical systems (MEMS) technology. The process involves designing an electrostatic vertically comb-driven actuator and utilizing a self-alignment process to produce a height difference between the movable comb structure and the fixed comb structure of the micromirror. To improve the stability of the micromirror, we propose four instability models in micromirror operation with the quasi-static driving principle and structure of the micromirror considered, which can provide a basic guarantee for the performance of vertical comb actuators. This analysis pinpoints factors leading to instability, including the left and right gap of the movable comb, the torsion beams of the micromirror, and the comb-to-beams distance. Ultimately, the voltages at which device failure occurs can be determined. We successfully fabricated a one-dimensional micromirror featuring a 0.8 mm mirror diameter and a 30 μm device layer thickness. The height difference between the movable and fixed comb structures was 10 μm. The micromirror was able to achieve a static mechanical angle of 2.25° with 60 V@DC. Stable operation was observed at voltages below 60 V, in close agreement with the theoretical calculations and simulations. At the driving voltage of 80 V, we observed the longitudinal displacement movement of the comb fingers. Furthermore, at a voltage of 129 V, comb adhesion occurred, resulting in device failure. This failure voltage corresponds to the lateral torsional failure voltage.

In integrated circuits (ICs), the parasitic capacitance is one of the crucial factors that degrade the circuit dynamic performance; for instance, it reduces the operating frequency of the circuit. Eliminating the parasitic capacitance in organic transistors is notoriously challenging due to the inherent tradeoff between manufacturing costs and interlayer alignment accuracy. Here, we overcome such a limitation using a cost‐effective method for fabricating organic thin‐film transistors and rectifying diodes without redundant electrode overlaps. This is achieved by placing all electrodes horizontally and introducing sub‐100 nm gaps for separation. A representative small‐scale IC consisting of five‐stage ring oscillators based on the obtained nonparasitic transistors and diodes is fabricated on flexible substrates, which performs reliably at a low driving voltage of 1 V. Notably, the oscillator exhibits signal propagation delays of 5.8 μs per stage at a supply voltage of 20 V when utilizing pentacene as the active layer. Since parasitic capacitance has been a common challenge for all types of thin‐film transistors, our approach may pave the way toward the realization of flexible and large‐area ICs based on other emerging and highly performing semiconductors. The proposed dual self‐alignment technique enables the realization of a nanogap that effectively isolates the gate from the source/drain electrodes in organic thin‐film transistors and the cathode from the anode in rectifying diodes. Consequently, the parasitic capacitance of these devices is completely eliminated. This breakthrough permits the development of small‐scale organic integrated circuits free of parasitic capacitance, which can be fabricated on flexible substrates.

Analytic alignment is a type of self-alignment for a Strapdown inertial navigation system (SINS) that is based solely on two non-collinear vectors, which are the gravity and rotational velocity vectors of the Earth at a stationary base on the ground. The attitude of the SINS with respect to the Earth can be obtained directly using the TRIAD algorithm given two vector measurements. For a traditional analytic coarse alignment, all six outputs from the inertial measurement unit (IMU) are used to compute the attitude. In this study, a novel analytic alignment method called selective alignment is presented. This method uses only three outputs of the IMU and a few properties from the remaining outputs such as the sign and the approximate value to calculate the attitude. Simulations and experimental results demonstrate the validity of this method, and the precision of yaw is improved using the selective alignment method compared to the traditional analytic coarse alignment method in the vehicle experiment. The selective alignment principle provides an accurate relationship between the outputs and the attitude of the SINS relative to the Earth for a stationary base, and it is an extension of the TRIAD algorithm. The selective alignment approach has potential uses in applications such as self-alignment, fault detection, and self-calibration.

Cross-lingual sentiment analysis plays a crucial role in accurately interpreting emotions across diverse linguistic contexts. However, performance disparities remain a major challenge, particularly in fewer-resource (including medium-resource and low-resource) languages. This study proposes an adaptive self-alignment framework for large language models, incorporating novel data augmentation techniques and transfer learning strategies to mitigate resource imbalances. Comprehensive experiments conducted on 11 languages demonstrate that our approach consistently surpasses state-of-the-art baselines, achieving an average F1-score improvement of 7.35 points. Notably, our method exhibits exceptional effectiveness in fewer-resource languages, significantly narrowing the performance gap between fewer- and high-resource settings. With robust domain adaptation capabilities and strong potential for real-world industrial applications, this research establishes a new benchmark for multilingual sentiment analysis, advancing the development of more inclusive and equitable natural language processing solutions.