Search results

A large-scale detection system with more data in short time bins, small dead space and small signal identification is the ideology the scientists pursuing. These proposed demands are able to be solved by 2.5 D integration. The substance of a 2.5 D integration is called silicon interposer, which consists of the through silicon via (TSV) and redistribution layer. However, the state-of-the-art silicon interposer is not able to sustain its own mechanical strength with the detector/readout array often sitting as standalone in large science facilities and fails to reduce the expansions on the installation of the components due to its insufficient thickness and size. This study aims to propose a moderation of current interposer with large-sized, standalone properties.

This paper proposes an interposer based on double-sided silicon vias (DSSVs) interconnection. Unlike conventional interposer that is interconnected by TSVs, DSSVs interposer is interconnected by top vias (T-vias) and bottom vias (B-vias).

The fabrication process of DSSVs interposer is introduced, and the superiority of the double-sided interconnection process with two etch-stop layers is described in detail. The impact of different T-vias depth on DSSVs interconnections in the same wafer is discussed and two times PI opening processes are proposed to eliminate air bubbles in the B-via. The relationship between the interposer thickness and warpage is studied by finite element analysis simulation and experiment. The prototype of the DSSVs interposer with a size of 100  × 100 mm and a thickness of 318.2 µm is fabricated, and electrical tests including short tests and continuity tests are carried out.

This paper proposes a large-sized and stand-alone interposer based on DSSVs interconnection.

In the context of fixed-wing aircraft wing assembly, there is a need for a rapid and precise measurement technique to determine the center distance between two double-hole components. This paper aims to propose an optical-based spatial point distance measurement technique using the spatial triangulation method. The purpose of this paper is to design a specialized measurement system, specifically a spherically mounted retroreflector nest (SMR nest), equipped with two laser displacement sensors and a rotary encoder as the core to achieve accurate distance measurements between the double holes.

To develop an efficient and accurate measurement system, the paper uses a combination of laser displacement sensors and a rotary encoder within the SMR nest. The system is designed, implemented and tested to meet the requirements of precise distance measurement. Software and hardware components have been developed and integrated for validation.

The optical-based distance measurement system achieves high precision at 0.04 mm and repeatability at 0.02 mm within a range of 412.084 mm to 1,590.591 mm. These results validate its suitability for efficient assembly processes, eliminating repetitive errors in aircraft wing assembly.

This paper proposes an optical-based spatial point distance measurement technique, as well as a unique design of a SMR nest and the introduction of two novel calibration techniques, all of which are validated by the developed software and hardware platform.

Dysarthria is a neuromotor speech disorder caused by neuromuscular disturbances that affect one or more articulators resulting in unintelligible speech. Though inter-phoneme articulatory variations are well captured by formant frequency-based acoustic features, these variations are expected to be much higher for dysarthric speakers than normal. These substantial variations can be well captured by placing sensors in appropriate articulatory position. This study focuses to determine a set of articulatory sensors and parameters in order to assess articulatory dysfunctions in dysarthric speech.

The current work aims to determine significant sensors and parameters associated using motion path and correlation analyzes on the TORGO database of dysarthric speech. Among eight informative sensor channels and six parameters per channel in positional data, the sensors such as tongue middle, back and tip, lower and upper lips and parameters (y, z, φ) are found to contribute significantly toward capturing the articulatory information. Acoustic and positional data analyzes are performed to validate these identified significant sensors. Furthermore, a convolutional neural network-based classifier is developed for both phone-and word-level classification of dysarthric speech using acoustic and positional data.

The average phone error rate is observed to be lower, up to 15.54% for positional data when compared with acoustic-only data. Further, word-level classification using a combination of both acoustic and positional information is performed to study that the positional data acquired using significant sensors will boost the performance of classification even for severe dysarthric speakers.

The proposed work shows that the significant sensors and parameters can be used to assess dysfunctions in dysarthric speech effectively. The articulatory sensor data helps in better assessment than the acoustic data even for severe dysarthric speakers.

The purpose of this paper is to focus on “how to create value from collaborative innovation,” which is a core question when companies plan open-innovation initiatives. China’s Huawei Technologies is taken as the main case study, with other companies’ practices as further examples to elaborate and validate a new yet practical model.

This paper is based on the direct experience over many years of two Huawei technology executives – the very recent head of the technology cooperation department and the current manager of the same unit.

This study provides a spiral four-stage model, named SWIM, with each stage being a decision guided by a 2 × 2 matrix. These stages, named scope, weave, identify and modularize, try to balance resource allocation toward a foreseeable value, though it might be long term.

The research is primarily based on one company. The validity of its recommended model can be tested only after other companies have applied it.

The research offers a practical framework for how companies can improve their open innovation.

Large companies are important players in innovation networks. Improving the ability of large companies to operate open innovation will help many other companies and the society as a whole.

The proposed model is original and provides insights from China and is not a traditional source of management innovation. The paper will also help Western readers get a better understanding of management in what will soon be the world’s largest economy.

How to free the potential power of the capital market while simultaneously protecting the investors is critical in equity-based crowdfunding. To realize these goals, the purpose of this study was to investigate the value of information disclosure and leader-follower mechanism which have been widely adopted by crowdfunding platforms.

Based on the Elaboration Likelihood Model (ELM), a research framework was developed. Then, the authors conducted an in-depth exploratory empirical study of Dajiatou (www.dajiatou.com) which is a typical equity-based crowdfunding service provider in China. Independent-samples t-test and linear regression were used to uncover the value of project information disclosure and the lead investor in terms of fundraising performance improvement.

First, the quality of entrepreneurial team information, especially the ratio of full-time staff, staff number and enterprise business age, significantly improve fundraising performance. Second, entrepreneurs’ behaviors, including project updates and project video, play important roles in crowdfunding. Third, whether or not the project has a lead investor, leader’s credibility information and his/her advocacy behaviors – percentage of their investment, identity certification, investment experience and comments for projects – are important factors affecting fundraising performance.

The authors are one of the firsts to apply ELM to investigate the effects of diverse information on fundraising performance in equity-based crowdfunding. The value of lead investor which has been ignored in prior research was studied through second-hand data.

First, an equity-based crowdfunding platform should request the entrepreneur to disclose project quality-related information with more details. Second, crowdfunding platforms should set a high qualifications level for lead investor, and limit the lead investor’s committed percentage in a specific project.

This paper extended the research in crowdfunding by uncovering the value of information disclosure and lead investor based on ELM theory.

The main aim of this paper was to study the self-lubricating behavior and failure mechanism of silver-rich solid film for in-depth analyzing of the friction and wear property of TiAl-10 wt. per cent Ag self-lubricating composite.

The friction and wear property of TiAl-10 wt. per cent Ag self-lubricating composite sliding against Si3N4 ball was tested under the testing conditions of ball-on-disk wear system. Field emission scanning electron microscopy and electron probe microanalyzer were used to analyze the surface morphology of silver-rich solid film. The main element contents were tested by energy dispersive spectroscopy. Silver phase on wear scar could be well identified using X-ray photo-electron spectroscopy. The theory calculation of shearing stress on wear scar was executed to discuss the local failure mechanism of silver-rich solid film. The lubricating role of silver was also discussed to analyze the anti-friction and anti-wear behavior of silver-rich solid film.

The friction coefficients and wear rates of TASC gradually reduced at 0-65 min, and approached to small values (0.31 in friction coefficient and 3.10×104 mm3N-1m-1 in wear rate) at 65-75 min. The excellent friction and wear behavior of TASC was mainly attributed to the lubricating property of silver-rich film at 65-75 min. At 12→20 N, surface shearing stress increased up to 146.31 MPa, and exceeded more than the shearing strength (125 MPa) of silver-rich film, which caused the propagating of fatigue crack and the destroying of silver-rich film, leading to high friction and severe wear.

It is important that the self-lubricating behavior and local failure of solid film is explored for further understanding the friction and wear property of TiAl alloys.

This paper aims to present an iterative path-following method with joint limits to solve the problem of large computation cost, movement exceeding joint limits and poor path-following accuracy for the path planning of hyper-redundant snake-like manipulator.

When a desired path is given, new configuration of the snake-like manipulator is obtained through a geometrical approach, then the joints are repositioned through iterations until all the rotation angles satisfy the imposed joint limits. Finally, a new arrangement is obtained through the analytic solution of the inverse kinematics of hyper-redundant manipulator. Finally, simulations and experiments are carried out to analyze the performance of the proposed path-following method.

Simulation results show that the average computation time is 0.1 ms per step for a hyper-redundant manipulator with 12 degrees of freedom, and the deviation in tip position can be kept below 0.02 mm. Experiments show that all the rotation angles are within joint limits.

Currently , the manipulator is working in open-loop, the elasticity of the driving cable will cause positioning error. In future, close-loop control based on real-time attitude detection will be used in in combination with the path-following method to achieve high-precision trajectory tracking.

Through a series of iterative processes, the proposed method can make the manipulator approach the desired path as much as possible within the joint constraints with high precision and less computation time.

Based on the person-environment (P-E) fit theory, this study aims to explore the effect of customer mistreatment on the reduced service performance of hospitality employees mediated by person-job (P-J) fit perceptions and moderated by job crafting.

The authors tested this study’s hypotheses with a nine-day diary study involving 83 service employees located in Lanzhou, China; a total of 548 daily surveys were completed. The authors used multilevel structural equation modeling to analyze the data.

Employees who experienced daily customer mistreatment suffered diminished P-J fit perceptions, leading to lower levels of service performance the next day. In addition, job crafting significantly buffered the impact of customer mistreatment on P-J fit perceptions and the indirect impact of customer mistreatment on service performance through P-J fit perceptions.

Given the damaging effect that customer mistreatment has on service performance, where employees’ P-J fit perceptions are impaired, hotel managers should implement service competence improvement training programs and managerial preventions to reduce the possibility of customer mistreatment behavior. The moderating role of job crafting behavior suggests that managers should offer supportive practices (i.e. job autonomy) to encourage job crafting behaviors among employees.

This study reveals that individuals’ P-J fit perceptions can explain the damaging impacts of customer mistreatment on service performance, a finding that contributes valuable information to the literature on customer mistreatment and P-E fit. Second, this study also tests the impact of individuals’ job crafting behaviors in terms of mitigating the negative effect of customer mistreatment. Finally, this study’s findings broaden the scope of predictors of P-J fit perceptions by revealing that customer mistreatment can pose a threat to hospitality employees’ P-J fit perceptions.

The purpose of this paper is to extend the usage of stroke gestures in manipulation tasks to make the interaction between human and robot more efficient.

In this paper, a set of stroke gestures is designed for typical manipulation tasks. A gesture recognition and parameter extraction system is proposed to exploit the information in stroke gestures drawn by the users.

The results show that the designed gesture recognition subsystem can reach a recognition accuracy of 99.00 per cent. The parameter extraction subsystem can successfully extract parameters needed for typical manipulation tasks with a success rate about 86.30 per cent. The system shows an acceptable performance in the experiments.

Using stroke gesture in manipulation tasks can make the transmission of human intentions to the robots more efficient. The proposed gesture recognition subsystem is based on convolutional neural network which is robust to different input. The parameter extraction subsystem can extract the spatial information encoded in stroke gestures.

The author designs stroke gestures for manipulation tasks which is an extension of the usage of stroke gestures. The proposed gesture recognition and parameter extraction system can make use of stroke gestures to get the type of the task and important parameters for the task simultaneously.

This paper aims to present a pipeline to progressively deal with the online external parameter calibration and estimator initialization of the Stereo-inertial measurement unit (IMU) system, which does not require any prior information and is suitable for system initialization in a variety of environments.

Before calibration and initialization, a modified stereo tracking method is adopted to obtain a motion pose, which provides prerequisites for the next three steps. Firstly, the authors align the pose obtained with the IMU measurements and linearly calculate the rough external parameters and gravity vector to provide initial values for the next optimization. Secondly, the authors fix the pose obtained by the vision and restore the external and inertial parameters of the system by optimizing the pre-integration of the IMU. Thirdly, the result of the previous step is used to perform visual-inertial joint optimization to further refine the external and inertial parameters.

The results of public data set experiments and actual experiments show that this method has better accuracy and robustness compared with the state of-the-art.

This method improves the accuracy of external parameters calibration and initialization and prevents the system from falling into a local minimum. Different from the traditional method of solving inertial navigation parameters separately, in this paper, all inertial navigation parameters are solved at one time, and the results of the previous step are used as the seed for the next optimization, and gradually solve the external inertial navigation parameters from coarse to fine, which avoids falling into a local minimum, reduces the number of iterations during optimization and improves the efficiency of the system.