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This paper aims to design a magnetostrictive tactile sensor for surface depth detection. Unlike the human finger, although most tactile sensors have high sensitivity to pressure, they cannot detect millimeter-level depth information on the surface of objects precisely. To enhance the ability to detect surface depth information, a piezomagnetic sensor combining inverse magnetostrictive effect and bionic structure is developed in this paper.

A magnetostrictive tactile sensor based on Galfenol [(Fe₈₃Ga₁₇)_99.4B_0.6] is designed and studied for surface depth measurement. The optimal structure of the sensor is determined by experiment and theory. The test platforms for static and dynamic characteristics are set up. The static and the dynamic sensing performance of the sensor are studied experimentally.

The sensor can detect 0–2 mm depth change with a sensitivity of 91.5 mV/mm. A resolution of 50 µm can be achieved in the depth direction. In 50 cycles of loading and unloading tests, the maximum error of the sensor output voltage amplitude is only 2.23%.

The sensor can measure the depth information of object surface precisely with good repeatability through sliding motion and provide reference for object surface topography detection.

This paper aims to discover the mathematical model for Q235 carbon steel corrosion date acquired in the initial stage of atmospheric corrosion using electrical resistance probe.

In this paper, mathematical approaches are used to construct a classification model for atmospheric environmental elements and material corrosion rates.

Results of the experiment show that the corrosion data can be converted into corrosion depth for calculating corrosion rate to obtain corrosion kinetics model and conform corrosion acceleration phase. Combined with corresponding atmospheric environmental elements, a real time grade subdivision model for corrosion rate can be constructed.

These mathematical models constructed by real time corrosion data can be well used to research the characteristics about initial atmospheric corrosion of Q235 carbon steel.

Gesture recognition plays an important role in many fields such as human–computer interaction, medical rehabilitation, virtual and augmented reality. Gesture recognition using wearable devices is a common and effective recognition method. This study aims to combine the inverse magnetostrictive effect and tunneling magnetoresistance effect and proposes a novel wearable sensing glove applied in the field of gesture recognition.

A magnetostrictive sensing glove with function of gesture recognition is proposed based on Fe-Ni alloy, tunneling magnetoresistive elements, Agilus30 base and square permanent magnets. The sensing glove consists of five sensing units to measure the bending angle of each finger joint. The optimal structure of the sensing units is determined through experimentation and simulation. The output voltage model of the sensing units is established, and the output characteristics of the sensing units are tested by the experimental platform. Fifteen gestures are selected for recognition, and the corresponding output voltages are collected to construct the data set and the data is processed using Back Propagation Neural Network.

The sensing units can detect the change in the bending angle of finger joints from 0 to 105 degrees and a maximum error of 4.69% between the experimental and theoretical values. The average recognition accuracy of Back Propagation Neural Network is 97.53% for 15 gestures.

The sensing glove can only recognize static gestures at present, and further research is still needed to recognize dynamic gestures.

A new approach to gesture recognition using wearable devices.

This study has a broad application prospect in the field of human–computer interaction.

The sensing glove can collect voltage signals under different gestures to realize the recognition of different gestures with good repeatability, which has a broad application prospect in the field of human–computer interaction.

The purpose of this paper is to examine the relationships between CEO narcissism and strategic decision-making (SDM) processes (decision comprehensiveness and decision speed), and to explore the mediating role of top management team (TMT) members’ participation in decision making and the moderating role of TMT power distance.

Data were collected from a multisource, time-lagged survey of 103 CEOs and their corresponding TMT members in China. Structural equation modeling was used to test the hypothesized relationships.

The results indicated that CEO narcissism was negatively related to decision comprehensiveness and positively related to decision speed. These relationships were mediated by TMT members’ participation in decision making, especially when TMT power distance was high.

The results show the potential negative effects of CEOs’ narcissistic personality and suggest ways to attenuate it by increasing TMT participation and decreasing TMT power distance.

This study is an initial attempt to empirically examine how and under what conditions CEOs’ narcissism is a barrier to more comprehensive and more deliberate (slower) SDM.

The credit card business has been one of the key businesses for banks in Taiwan. The purpose of this paper is to use competitive dynamics and structured context analysis (SCA) to explore the competition relationships among market, resources, and strategies concerning the credit card issued banks in Taiwan.

The market commonality and resource similarity analysis of competitive dynamics in the first stage obtained the competitive mapping of four major credit card issue banks, as well as the differences of competition strategy. In the second stage, 1,968 pieces of data on credit card news from 2013 to 2014 were collected. SCA was used to analyze the competitive action, competitive response, number of responses, response lag, and response order.

The competitor mapping and four hypothesis obtained from competitive dynamics correspond to the credit card competition strategy, as obtained from SCA.

This research combined competitive dynamics and SCA to analyze the credit cards market in Taiwan. The research model could be used in the other financial market.