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The aim of this study is to explore students' expectations and perceived effectiveness of computer-assisted review tools, and the differences in reliability and validity between human evaluation and automatic evaluation, to find a way to improve students' English writing ability.

Based on the expectancy disconfirmation theory (EDT) and Intelligent Computer-Assisted Language Learning (ICALL) theory, an experiment is conducted through the observation method, semistructured interview method and questionnaire survey method. In the experiment, respondents were asked to write and submit four essays on three online automated essay evaluation (AEE) systems in total, one essay every two weeks. Also, two teacher raters were invited to score the first and last papers of each student. The respondents' feedbacks were investigated to confirm the effectiveness of the AEE system; the evaluation results of the AEE systems and teachers were compared; descriptive statistics was used to analyze the experimental data.

The experiment revealed that the respondents held high expectations for the computer-assisted evaluation tools, and the effectiveness of computer scoring feedback on students was higher than that of teacher scoring feedback. Moreover, at the end of the writing project, the students' independent learning ability and English writing ability were significantly improved. Besides, there was a positive correlation between students' initial expectations of computer-assisted learning tools and the final evaluation of learning results.

The innovation lies in the use of observation methods, questionnaire survey methods, data analysis, and other methods for the experiment, and the combination of deep learning theory, EDT and descriptive statistics, which has particular reference value for future works.

This paper aims to propose a biologically inspired processing architecture to recognize and classify fabrics with respect to the weave pattern (fabric texture) and yarn color (fabric color).

By using the fabric weave patterns image identification system, this study analyzed the fabric image based on the Hierarchical-MAX (HMAX) model of computer vision, to extract feature values related to texture of fabric. Red Green Blue (RGB) color descriptor based on opponent color channels simulating the single opponent and double opponent neuronal function of the brain is incorporated in to the texture descriptor to extract yarn color feature values. Finally, support vector machine classifier is used to train and test the algorithm.

This two-stage processing architecture can be used to construct a system based on computer vision to recognize fabric texture and to increase the system reliability and accuracy. Using this method, the stability and fault tolerance (invariance) was improved.

Traditionally, fabric texture recognition is performed manually by visual inspection. Recent studies have proposed automatic fabric texture identification based on computer vision. In the identification process, the fabric weave patterns are recognized by the warp and weft floats. However, due to the optical environments and the appearance differences of fabric and yarn, the stability and fault tolerance (invariance) of the computer vision method are yet to be improved. By using our method, the stability and fault tolerance (invariance) was improved.

The purpose of this paper is to attempt to study the failure mechanism of BGA (ball grid array) Cu wire bond ball lift and specifically focused on substrate outgassing’s impact on Cu wire bonding quality and reliability.

The Galvanic corrosion theory has been widely adopted in explaining the failure mechanism of Cu ball bond lift issue during reliability test or field application in the presence of moisture. In this study, ion chromatography was performed on BGA substrate halogen analysis. EDX (energy-dispersive X-ray spectroscopy) was also used to detect the contaminant’s element at the bottom surface of a window clamp. Further FTIR (Fourier transform infrared spectroscopy) analysis verified that the contamination is from substrate outgassing during wire bonding. A new window clamp design proved effective in reducing the negative impact from substrate outgassing during wire bonding.

The solder mask in a fresh substrate contains a chlorine element. The chlorine can be detected in the BGA substrate outgassing during wire bonding by FTIR and EDX analyses, which have a negative impact on the Cu wire bonding. The window clamp with a larger opening can reduce the negative impact of the Cu wire bonding from the BGA substrate outgassing.

Because of the limitation of time and resources, bonding pad surface contamination from substrate outgassing and its correlation with Cu bonding ball lift failure after reliability test will be studied in depth later.

The BGA substrate outgassing has negative impacts on Cu wire bondability. A window clamp with a larger opening can reduce the negative impact from substrate outgassing.

Excellent obstacle surmounting performance is essential for the robotic vehicles in uneven terrain. However, existing robotic vehicles depend on complex mechanisms or control algorithms to surmount an obstacle. Therefore, this paper aims to propose a new simple configuration of an all-terrain robotic vehicle with eight wheels including four-swing arms.

This vehicle is driven by distributed hydraulic motors which provide high mobility. It possesses the ability to change the posture by means of cooperation of the four-swing arms. This ensures that the vehicle can adapt to complex terrain. In this paper, the bionic mechanism, control design and steering method of the vehicle are introduced. Then, the kinematic model of the center of gravity is studied. Afterward, the obstacle surmounting performance based on a static model is analyzed. Finally, the simulation based on ADAMS and the prototype experiment is carried out.

The experiment results demonstrate that the robotic vehicle can surmount an obstacle 2.29 times the height of the wheel radius, which verifies the feasibility of this new configuration. Therefore, this vehicle has excellent uneven terrain adaptability.

This paper proposes a new configuration of an all-terrain robotic vehicle with four-swing arms. With simple mechanism and control algorithms, the vehicle has a high efficiency of surmounting an obstacle. It can surmount a vertical obstacle 2.29 times the height of the wheel radius.

The purpose of this study is to describe the present taxonomy of money, summarize potential central bank digital currency (CBDC) regimes that central banks worldwide could adopt and explore the implications of the introduction of each of these CDBC regimes for money laundering through the lens of the regulatory dialectic theory.

The methodology used in the analysis of significant recent events regarding the progress of central banks in establishing a CBDC and the implications for money laundering under a CBDC regime. This paper also reviews the literature regarding the Regulatory Dialectic to highlight potential innovative responses of money launderers to circumvent the controls generated through the implementation of a CBDC.

This study examines the impact of Kane’s regulatory dialectic paradigm on the feasibility of money laundering under a CBDC regime and identifies potential avenues that would be available for those seeking to launder money, based on the form a CBDC would take.

This paper is unable as of yet to empirically evaluate anti-money laundering (AML) tactics under a CBDC regime as it has not yet been fully implemented.

Many central banks worldwide are evaluating the structure of and introduction of a CBDC. There are a number of forms that a CBDC could take, each of which has implications for individual privacy and for entities involved in AML efforts within financial institutions and the regulatory community. The paper has implications for AML experts who are considering how AML procedures would change under a CBDC regime.

The regulatory dialectic predicts that regulatory response reactive, rather than proactive when it comes to socially undesirable phenomena. As central banks and governments seek to divert economic activity away from the laundering of the proceeds of illicit activity, there are tradeoffs in terms of a loss of privacy. The regulatory dialectic predicts a corresponding innovative response of those who wish to undermine the controls generated through the establishment of a CBDC.

To the authors’ knowledge, this is the first paper to explore the impact of a potential CBDC on money laundering and the potential innovative circumventions within the paradigm of the Regulatory Dialectic.

The purpose of this paper was to attempt to confirm the root cause of wafer damage issue by heavy Al wire wedge bonding and propose some permanent solutions for it.

The infra red–optical beam-induced resistance change (IR-OBIRCH) analysis defines the position of an abnormal hotspot. A cross section and an scanning electron microscope (SEM) confirmed the wafer damage issue and its position. Based on the position of wafer damage, the wedge tool with different life and Al buildup was checked found to be on the wedge tool. Finite element analysis (FEA) modeling analysis and simulation experiment guarantee the Al buildup, and low wedge deformation thickness (WDT) can cause the wafer damage issue. Finally, design of experiment (DOE) experiments are designed to optimize wedge tool dimension and wedge-bond parameters to eliminate wafer damage issue.

Wafer damage issue caused the Vpwr-OUTPUT leakage issue by IR-OBIRCH analysis. Al buildup was found on wedge tool with different life and its size gets larger along with the increase in wedge tool life. Low WDT and bigger Al buildup can cause the wafer damage. Designing new wedge tool and parameters optimization can increase WDT.

Because of the limitation of time and resources, finite element method (FEM) modeling and wedge tool dimension could not be studied more deeply.

This paper sets an example on how to find out the root cause of wafer damage by a step-by-step analysis and put forward a quick solution accordingly for the issue.

Man has been seeking an ideal existence for a very long time. In this existence, justice, love, and peace are no longer words, but actual experiences. How ever, with the American preemptive invasion and occupation of Afghanistan and Iraq and the subsequent prisoner abuse, such an existence seems to be farther and farther away from reality. The purpose of this work is to stop this dangerous trend by promoting justice, love, and peace through a change of the paradigm that is inconsistent with justice, love, and peace. The strong paradigm that created the strong nation like the U.S. and the strong man like George W. Bush have been the culprit, rather than the contributor, of the above three universal ideals. Thus, rather than justice, love, and peace, the strong paradigm resulted in in justice, hatred, and violence. In order to remove these three and related evils, what the world needs in the beginning of the third millenium is the weak paradigm. Through the acceptance of the latter paradigm, the golden mean or middle paradigm can be formulated, which is a synergy of the weak and the strong paradigm. In order to understand properly the meaning of these paradigms, however, some digression appears necessary.

Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction for EIT is a nonlinear problem. A generalized inverse operator is usually ill-posed and ill-conditioned. Therefore, the solutions for EIT are not unique and highly sensitive to the measurement noise.

This paper develops a novel image reconstruction algorithm for EIT based on patch-based sparse representation. The sparsifying dictionary optimization and image reconstruction are performed alternately. Two patch-based sparsity, namely, square-patch sparsity and column-patch sparsity, are discussed and compared with the global sparsity.

Both simulation and experimental results indicate that the patch based sparsity method can improve the quality of image reconstruction and tolerate a relatively high level of noise in the measured voltages.

EIT image is reconstructed based on patch-based sparse representation. Square-patch sparsity and column-patch sparsity are proposed and compared. Sparse dictionary optimization and image reconstruction are performed alternately. The new method tolerates a relatively high level of noise in measured voltages.

This paper aims to investigate the equivalent relationship between accelerated corrosion tests and real environmental spectrum of suspenders in long-span suspension bridge considering multiple factors action.

Based on Faraday's law, corrosion current was used as a measure of metal corrosion, and the equivalent conversion relationship between laboratory environment and real service environment was established. The equivalent conversion method for bridge structural steel had been determined under different temperature, humidity, pH value and NaCl concentration conditions. The compilation of environmental spectra for large span bridges considering multiple factors and the principle of equivalent conversion have been proposed.

Environmental factors, including temperature, humidity, pH value and NaCl concentration, have significant impact on the corrosion degree of suspension steel wires, and only considering these two factors for equivalent conversion cannot accurately reflect the true service environment of the bridge. The 33.8-h salt spray accelerated corrosion test using the standard conditions can be equivalent to one year of suspenders corrosion in a real service environment.

The equivalent accelerated corrosion method for steel wires proposed in this study can effectively predict the corrosion degree of the suspenders, which has been verified to be correct and can provide theoretical guidance for the development of corrosion test plans for steel wires and engineering technical basis for anti-corrosion control and calendar life research of suspension bridge suspenders.

Entrepreneurs and individual sellers heavily leverage their social ties embedded in social media, expressive or instrumental, to penetrate the market and achieve business success. However, the extant social commerce literature offers limited understanding on how different forms of buyer−seller social ties embedded in social media affect buyers' purchase behaviors. The study draws on the theoretical lens of social ties and proposes an integrative theoretical framework to understand the direct and indirect influences of expressive and instrumental ties (ExTSM and InTSM) between buyers and sellers on buyers' purchase intention (PI) in social commerce.

The authors first validated the measures of ExTSM and InTSM with survey data from 166 Weibo commerce buyers. They then tested their theoretical framework and hypotheses with survey data from 246 buyer−seller dyads in WeChat commerce.

With a buyer-centric view, (1) ExTSM and InTSM, respectively, had a direct negative and a positive influence on PI; (2) both trust and perceived product value displayed inconsistent mediation effects on the negative relationship between ExTSM and PI; and (3) only perceived product value mediated the positive influence of InTSM on PI. From sellers' viewpoint, (1) their ExTSM and InTSM with buyers were mixed up, and (2) the mingled social ties negatively impacted buyers' purchase intention.

The findings of the study advance the theoretical understanding of social commerce and offer practical guidance for small and medium-sized enterprises to effectively utilize social media for business purposes.