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This study aimed to explore the underlying reasons for student silence in EMI classrooms and identify the coping strategies employed by students and teachers.

Employing qualitative case study methods, in-depth semi-structured interviews and focus group discussions were conducted with both teachers and students. Thematic analysis was used for the findings.

Thematic analysis of the data revealed four primary reasons for student silence, and several effective coping strategies used by students and teachers to mitigate this challenge.

The findings provide a comprehensive understanding of the phenomenon of silence among Chinese undergraduate students in English as a medium of instruction classrooms and offer valuable insights to students and teachers to adapt and succeed in these challenging environments.

The originality of this study lies in the fact that this is among the few studies conducted on students from a foreign branch campus of an American university in China that explores the explores the phenomenon of silence of Chinese students in such universities.

Introduction: The application of artificial intelligence (AI) can substantially enhance both short- and long-term decision-making in human resource management (HRM) practices. However, academic research fails to address the dark side of AI in confluence with HRM and primarily paints a bright picture of the advantages of AI.

Purpose: The current research emphasises the challenges faced in the HRM domain in applying AI in HRM practices and further discusses the future path to maximise the effect of AI on HRM.

Methodology: The study rigorously surveyed secondary sources like the journal papers, consultant reports and other databases to critically examine the challenges encountered in applying AI in HRM practices.

Findings: Analysis of the above-mentioned sources shows that AI algorithm might bring routinisation of work. HRM ethics, data safety and integrity, biased algorithm from the programmer, fewer data to train the AI model, lack of technical skills of HR executive, neglecting values, and ignoring the creative thinking by employees are a few aspects that might cause difficulty in the adaptation of AI in the HRM domain. As a consequence, there could be unnecessary extra monitoring of employee behaviour, which in turn could lead to loss of workplace well-being and trimming of the human element in HRM.

Practical Implications: This study adds value by focusing on the challenges and suggests the path for robust HRM practices; because, the biased decision-making by AI could potentially lead to improper decision-making by the top management, and in turn, the sustainability of a firm could be at stake.

Differing from previous studies trying to solve the electromagnetic compatibility (EMC) issue by addressing single factor, this study aims to combine measures of shielding, filtering and grounding to design parameters with the Taguchi method at the beginning of product design to come up with the optimal parameter combination.

EMC-related performance such as radiated emission, conduction interference and electrical fast transient/burst immunity (EFT) are response variables, whereas the printed circuit board and mechanic design-relevant parameters are considered as control factors. The noise factors are peripherals used together with the tablet.

The optimal design parameter matrix based on results from the application and integration of multivariate analysis method of principal component grey relation and technique for order preference by similarity to ideal solution suggests 14 grounding screw holes, cooling aperture of casing at diameter of 3 mm and staggered layout and 300O filter located at source of noise. Validation of this matrix shows around 10, 1 and 8 per cent improvement in radiation, conduction interference and EFT immunity.

The multivariate quality parameters’ design method proposed by this study improves EMC characteristics of products and meets the design specification required by customer, accelerating electronic product research and development process and complying with electromagnetic interference test regulations set forth by individual country.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

This paper is aimed to study the design of a miniaturized filter with tri-band characteristics. In this paper, perturbation is used to realize circuit miniaturization and multi-band by exploiting the inductive property. During this process, vias are added for twofold benefit, namely, circuit miniaturization and enhanced frequency selectivity at high frequency. Thus, with the introduction of the shorting via, the single-band dual-mode bandpass filter is converted into a tri-band filter with a smaller electrical size.

This paper presents the design and characterization of a miniaturized two-port filter with tri-band operating characteristics. The proposed filter is constructed using a square patch resonator operating at 5.2 GHz with a capacitively coupled feed configuration. A square perturbation is added to the corner of the square patch to achieve diagonal symmetry and to excite dual mode. The perturbation offers a sharp transmission zero defining bandwidth of the proposed filter. In addition, a shorting post is introduced to achieve an 88% size reduction by lowering the operating frequency to 1.8 GHz.

The prototype filter has insertion less than 1.2 dB and return loss better than 12 dB throughout all the realized frequency bands. The prototype filter is fabricated and the simulation results are validated using experimental measurements. The realized fractional bandwidths of the proposed bandpass filter are 11/5.6/1 at 1.8/4.6/5.85 GHz, respectively. The quality factor of the proposed antenna is greater than 80 and a peak Q-factor of 387 is realized at 5.85 GHz. The high Q-factor indicates low loss and improved selectivity. The rejection levels in the stopband are greater than 20 dB.

The results indicate that the proposed filter is a suitable choice for low-power small-scale wireless systems operating in the microwave bands. The realized filter has the smallest footprint of 0.36λ_eff  × 0.19λ_eff where λ_eff is the effective wavelength calculated at the lowest frequency of operation.

This paper aims to design a dual mode X-band substrate integrated waveguide (SIW) bandpass filter in the conventional SIW structure. A pair of back-to-back square and split ring resonator is introduced in the single-layer SIW bandpass filter. The various coupling configurations of SIW bandpass filter using split square ring slot resonator is designed to obtain dual resonant mode in the passband. It is shown that the measured results agree with the simulated results to meet compact size, lower the transmission coefficient, better reflection coefficient, sharp sideband rejection and minimal group delay.

A spurious suppression of wideband response is suppressed using an open stub in the transmission line. The width and length of the stub are tuned to suppress the wideband spurs in the stopband. The measured 3 dB bandwidth is from 8.76 to 14.24 GHz with a fractional bandwidth of 48.04% at a center frequency of 11.63 GHz, 12.59 GHz. The structure is analyzed using the equivalent circuit model, and the simulated analysis is based on an advanced design system software.

This paper discusses the characteristics of resonator below the waveguide cut-off frequency with their working principles and applications. Considering the difficulties in combining the resonators with a metallic waveguide, a new guided wave structure – the SIW is designed, which is synthesized on a planar substrate with linear periodic arrays of metallized via based on the printed circuit board.

This study has investigated the wave propagation problem of the SIW loaded by square ring slot-loaded resonator. The electric dipole nature of the resonator has been used to achieve a forward passband in a waveguide environment. The proposed filters have numerous advantages such as high-quality factor, low insertion loss, easy to integrate with the other planar circuits and, most importantly, compact size.