Culture and the way of granting job autonomy: Goal or execution?

Researchers have assumed that Westerners exercise higher job autonomy than Easterners. However, recent studies have reported mixed and even contradictory findings. The authors distinguish between two types of job autonomy, namely goal and execution autonomy, to examine the relevant cultural differences. The former denotes participation in setting work goals and making plans for meeting those goals, while the latter denotes the ability to complete tasks flexibly. Four studies with a total sample of 1192 participants working in financial or insurance companies were conducted. Study 1a generated items for a new measure of the two types of job autonomy and explored its factor structure. Studies 1b and 1c verified its construct validity and predictive capacity. Study 2 confirmed the structural and metric equivalence of the measure between samples from the United Kingdom and China. The results of Study 2 suggested that the Chinese workers were likely to have high execution autonomy but low goal autonomy, whereas the British workers tended to have high goal autonomy but low execution autonomy. The theoretical and practical implications of job autonomy in cross-cultural contexts are discussed

Culture and the way of granting job autonomy: Goal or execution?

Researchers have assumed that Westerners exercise higher job autonomy than Easterners. However, recent studies have reported mixed and even contradictory findings. The authors distinguish between two types of job autonomy, namely goal and execution autonomy, to examine the relevant cultural differences. The former denotes participation in setting work goals and making plans for meeting those goals, while the latter denotes the ability to complete tasks flexibly. Four studies with a total sample of 1192 participants working in financial or insurance companies were conducted. Study 1a generated items for a new measure of the two types of job autonomy and explored its factor structure. Studies 1b and 1c verified its construct validity and predictive capacity. Study 2 confirmed the structural and metric equivalence of the measure between samples from the United Kingdom and China. The results of Study 2 suggested that the Chinese workers were likely to have high execution autonomy but low goal autonomy, whereas the British workers tended to have high goal autonomy but low execution autonomy. The theoretical and practical implications of job autonomy in cross-cultural contexts are discussed

Discrete crystal plasticity modelling of slip-controlled cyclic deformation and short crack growth under low cycle fatigue

For metals under fatigue, microplastic strain localisation leads to the formation of discrete slip bands, which contributes to the initiation and propagation of short cracks. In this paper, a discrete slip band model is introduced to investigate the slip-controlled cyclic deformation and short crack growth in a single crystal alloy. In conjunction with crystal plasticity and normal factor-based critical resolved shear stress, finite element simulations demonstrated the success of the discrete model in describing orientation-dependent cyclic stress-strain responses. The proposed approach is also capable of predicting slip-controlled short crack growth, based on element deletion technique and individual cumulative shear strain criterion

A fault diagnosis algorithm for analog circuits based on self-attention mechanism deep learning

Analog circuit is an essential part of the integrated circuit. One of the current research hotspots in integrated circuit testing is the detection of faults occurring in analog circuits and the accurate identification of fault types based on deep learning techniques. To address the difficulties in fault detection of analog integrated circuits, the advanced achievements of artificial intelligence in the field of image recognition and speech classification is referenced and an analog circuit fault detection idea based on a deep learning algorithm of self-attention mechanism is proposed, which can be used to detect faults in Sallen-Key low-pass filter circuits. The output signal is sampled into an audio signal and fed into an audio classification model based on a self-attentive transform network for training, testing, and optimization. The results show that fault detection based on the self-attentive mechanism audio classification has an average accuracy of 93. 1% and a maximum accuracy of 98. 1% . Nine different fault types can be detected. The model converges fast and can detect faults in analog circuits, which thoroughly verifies the feasibility of the proposed idea

Dual-Tree Complex Wavelet Transform and Twin Support Vector Machine for Pathological Brain Detection

Abstract: (Aim) Classification of brain images as pathological or healthy case is a key pre-clinical step for potential patients. Manual classification is irreproducible and unreliable. In this study, we aim to develop an automatic classification system of brain images in magnetic resonance imaging (MRI). (Method) Three datasets were downloaded from the Internet. Those images are of T2-weighted along axial plane with size of 256 ˆ 256. We utilized an s-level decomposition on the basis of dual-tree complex wavelet transform (DTCWT), in order to obtain 12s “variance and entropy (VE)” features from each subband. Afterwards, we used support vector machine (SVM) and its two variants: the generalized eigenvalue proximal SVM (GEPSVM) and the twin SVM (TSVM), as the classifiers. In all, we proposed three novel approaches: DTCWT + VE + SVM, DTCWT + VE + GEPSVM, and DTCWT + VE + TSVM. (Results) The results showed that our “DTCWT + VE + TSVM” obtained an average accuracy of 99.57%, which was not only better than the two other proposed methods, but also superior to 12 state-of-the-art approaches. In addition, parameter estimation showed the classification accuracy achieved the largest when the decomposition level s was assigned with a value of 1. Further, we used 100 slices from real subjects, and we found our proposed method was superior to human reports from neuroradiologists. (Conclusions) This proposed system is effective and feasible

Dual-Tree Complex Wavelet Transform and Twin Support Vector Machine for Pathological Brain Detection

Abstract: (Aim) Classification of brain images as pathological or healthy case is a key pre-clinical step for potential patients. Manual classification is irreproducible and unreliable. In this study, we aim to develop an automatic classification system of brain images in magnetic resonance imaging (MRI). (Method) Three datasets were downloaded from the Internet. Those images are of T2-weighted along axial plane with size of 256 ˆ 256. We utilized an s-level decomposition on the basis of dual-tree complex wavelet transform (DTCWT), in order to obtain 12s “variance and entropy (VE)” features from each subband. Afterwards, we used support vector machine (SVM) and its two variants: the generalized eigenvalue proximal SVM (GEPSVM) and the twin SVM (TSVM), as the classifiers. In all, we proposed three novel approaches: DTCWT + VE + SVM, DTCWT + VE + GEPSVM, and DTCWT + VE + TSVM. (Results) The results showed that our “DTCWT + VE + TSVM” obtained an average accuracy of 99.57%, which was not only better than the two other proposed methods, but also superior to 12 state-of-the-art approaches. In addition, parameter estimation showed the classification accuracy achieved the largest when the decomposition level s was assigned with a value of 1. Further, we used 100 slices from real subjects, and we found our proposed method was superior to human reports from neuroradiologists. (Conclusions) This proposed system is effective and feasible

Antenna Designs for CubeSats: A Review

Cube Satellites, aka CubeSats, are a class of nano satellites that have gained popularity recently, especially for those that consider CubeSats as an emerging alternative to conventional satellites for space programs. This is because they are cost-effective, and they can be built using commercial off-the-shelf components. Moreover, CubeSats can communicate with each other in space and ground stations to carry out many functions such as remote sensing (e.g., land imaging, education), space research, wide area measurements and deep space communications. Consequently, communications between CubeSats and ground stations is critical. Any antenna design for a CubeSat needs to meet size and weight restrictions while yielding good antenna radiation performance. To date, a limited number of works have surveyed, compared and categorised the proposed antenna designs for CubeSats based on their operating frequency bands. To this end, this paper contributes to the literature by focusing on different antenna types with different operating frequency bands that are proposed for CubeSat applications. This paper reviews 48 antenna designs, which include 18 patch antennas, 5 slot antennas, 4 dipole and monopole antennas, 3 reflector antennas, 3 reflectarray antennas, 5 helical antennas, 2 metasurface antennas and 3 millimeter and sub-millimeter wave antennas. The current CubeSat antenna design challenges and design techniques to address these challenges are discussed. In addition, we classify these antennas according to their operating frequency bands, e.g., VHF, UHF, L, S, C, X, Ku, K/Ka, W and mm/sub-mm wave bands and provide an extensive qualitative comparison in terms of their size, -10 dB bandwidths, gains, reflection coefficients, and deployability. The suitability of different antenna types for different applications as well as the future trends for CubeSat antennas are also presented.</p

A framework of modelling slip-controlled crack growth in polycrystals using crystal plasticity and XFEM

Short cracks tend to develop at high and irregular rates compared to macroscopic cracks, making the prediction of fatigue life a challenging task. In this work, a numerical framework combining crystal plasticity model and the Extended Finite Element Method (XFEM) is applied to study the slip-controlled short crack growth in a polycrystal superalloy RR1000. The model is calibrated from experiments and used to evaluate short crack growth paths and rates. Two fracture criteria are used and compared: the onset of fracture is controlled by the total and individual cumulative shear strain respectively, and the crack grows either perpendicular to the direction of maximum principal strain or along crystallographic directions

Detection of Left-Sided and Right-Sided Hearing Loss via Fractional Fourier Transform

In order to detect hearing loss more efficiently and accurately, this study proposed a new method based on fractional Fourier transform (FRFT). Three-dimensional volumetric magnetic resonance images were obtained from 15 patients with left-sided hearing loss (LHL), 20 healthy controls (HC), and 14 patients with right-sided hearing loss (RHL). Twenty-five FRFT spectrums were reduced by principal component analysis with thresholds of 90%, 95%, and 98%, respectively. The classifier is the single-hidden-layer feed-forward neural network (SFN) trained by the Levenberg–Marquardt algorithm. The results showed that the accuracies of all three classes are higher than 95%. In all, our method is promising and may raise interest from other researchers

A Survey on CubeSat Missions and Their Antenna Designs

CubeSats are a class of miniaturized satellites that have become increasingly popular in academia and among hobbyists due to their short development time and low fabrication cost. Their compact size, lightweight characteristics, and ability to form a swarm enables them to communicate directly with one another to inspire new ideas on space exploration, space-based measurements, and implementation of the latest technology. CubeSat missions require specific antenna designs in order to achieve optimal performance and ensure mission success. Over the past two decades, a plethora of antenna designs have been proposed and implemented on CubeSat missions. Several challenges arise when designing CubeSat antennas such as gain, polarization, frequency selection, pointing accuracy, coverage, and deployment mechanisms. While these challenges are strongly related to the restrictions posed by the CubeSat standards, recently, researchers have turned their attention from the reliable and proven whip antenna to more sophisticated antenna designs such as antenna arrays to allow for higher gain and reconfigurable and steerable radiation patterns. This paper provides a comprehensive survey of the antennas used in 120 CubeSat missions from 2003 to 2022 as well as a collection of single-element antennas and antenna arrays that have been proposed in the literature. In addition, we propose a pictorial representation of how to select an antenna for different types of CubeSat missions. To this end, this paper aims is to serve both as an introductory guide on CubeSats antennas for CubeSat enthusiasts and a state of the art for CubeSat designers in this ever-growing field.</p