36 research outputs found

    Accountants’ perceptions on the adoption of international financial reporting standards in Yemen

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    Developments in the global capital market have made the adoption of International Financial Reporting Standard (IFRSs) more significant than ever before.The purpose of this study is to examine the accountants’ perception of IFRSs adoption in Yemen. We also seek the accountants’ view on whether Yemen should adopt the IFRSs or not, and on the expected time taken to adopt the accounting standards. We also examine the difference in opinion between academicians and practitioners regarding the adoption of IFRSs. In this regard, this study carries out a survey of 48 Yemeni accounting postgraduate students in Malaysian public universities.We find that a majority of the respondents acknowledge the benefits of adopting IFRSs in Yemeni companies. Moreover, a majority of the respondents (82.9%) agree that Yemeni companies should adopt IFRSs. About 58.6% of respondents expect the period of IFRSs adoption in Yemen to be within three to 10 years, while 41.5% expect it to be more than 10 years.The results of this study may help policy-makers and the Yemeni Association of Certified Public Accountants (YACPA) make more precise decisions regarding IFRSs adoption in Yemen

    Accountants' Perceptions on the Adoption of International Financial Reporting Standards in Yemen

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    Developments in the global capital market have made the adoption of International Financial Reporting Standard (IFRSs) more significant than ever before. The purpose of this study is to examine the accountants' perception of IFRSs adoption in Yemen. We also seek the accountants' view on whether Yemen should adopt the IFRSs or not, and on the expected time taken to adopt the accounting standards. We also examine the difference in opinion between academicians and practitioners regarding the adoption of IFRSs. In this regard, this study carries out a survey of 48 Yemeni accounting postgraduate students in Malaysian public universities. We find that a majority of the respondents acknowledge the benefits of adopting IFRSs in Yemeni companies. Moreover, a majority of the respondents (82.9%) agree that Yemeni companies should adopt IFRSs. About 58.6% of respondents expect the period of IFRSs adoption in Yemen to be within three to 10 years, while 41.5% expect it to be more than 10 years. The results of this study may help policy-makers and the Yemeni Association of Certified Public Accountants (YACPA) make more precise decisions regarding IFRSs adoption in Yemen.    Keywords: IFRSs, accounting standard convergence, Yemen JEL Classifications: M4, M4

    Design of high gain base station antenna array for mm-wave cellular communication systems

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    Millimeter wave (mm-Wave) wireless communication systems require high gain antennas to overcome path loss effects and thereby enhance system coverage. This paper presents the design and analysis of an antenna array for high gain performance of future mm-wave 5G communication systems. The proposed antenna is based on planar microstrip technology and fabricated on 0.254 mm thick dielectric substrate (Rogers-5880) having a relative permittivity of 2.2 and loss tangent of 0.0009. The single radiating element used to construct the antenna array is a microstrip patch that has a configuration resembling a two-pronged fork. The single radiator has a realized gain of 7.6 dBi. To achieve the gain required by 5G base stations, a 64-element array antenna design is proposed which has a bore side gain of 21.2 dBi at 37.2 GHz. The 8 × 8, 8 × 16, and 8 × 32 antenna array designs described here were simulated and optimized using CST Microwave Studio, which is a 3D full-wave electromagnetic solver. The overall characteristics of the array in terms of reflection-coefficient and radiation patterns makes the proposed design suitable for mm-Wave 5G and other communication systems.Dr. Mohammad Alibakhshikenari acknowledges support from the CONEX-Plus programme funded by Universidad Carlos III de Madrid and the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 801538. In addition, this work was partially supported by Ministerio de Ciencia, Innovación y Universidades, Gobierno de España (Agencia Estatal de Investigación, Fondo Europeo de Desarrollo Regional -FEDER-, European Union) under the research grant PID2021-127409OB-C31 CONDOR. The authors also sincerely appreciate funding from Researchers Supporting Project number (RSP2023R58), King Saud University, Riyadh, Saudi Arabia

    Involvement of board chairmen in audit committees and earnings management: Evidence from Malaysia

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    This paper investigates the effect of the involvement of the board chairman in the audit committee (AC) on earnings management (EM). It examines Bursa Malaysia-listed companies with the lowest positive earnings for the years 2013 to 2015. The Modified Jones Model by Kasznik (1999) was used to determine discretionary accruals. An AC that includes its board chairman as an ordinary member is associated with greater discretionary accruals. However, a board chairman who is also the chairman of the AC does not seem to influence discretionary accruals. This paper supports the agency theory and policy-makers’ efforts to prevent board chairmen from sitting on ACs. It is the first study that uses the agency theory to describe the association between the board chairman’s involvement in the both AC and EM. This study alerts policy-makers, stakeholders and researchers to the influence of a board chairman serving on the AC in curbing EM. Furthermore, it provides empirical evidence that the majority of Malaysian companies whose board chairmen are involved in the AC appoint the chairman as an ordinary member of the AC. This indicates that executive directors may affect such actions. Hence, more policies are needed to improve AC independence

    Novel Privacy Preserving Non-Invasive Sensing-Based Diagnoses of Pneumonia Disease Leveraging Deep Network Model

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    This article presents non-invasive sensing-based diagnoses of pneumonia disease, exploiting a deep learning model to make the technique non-invasive coupled with security preservation. Sensing and securing healthcare and medical images such as X-rays that can be used to diagnose viral diseases such as pneumonia is a challenging task for researchers. In the past few years, patients’ medical records have been shared using various wireless technologies. The wireless transmitted data are prone to attacks, resulting in the misuse of patients’ medical records. Therefore, it is important to secure medical data, which are in the form of images. The proposed work is divided into two sections: in the first section, primary data in the form of images are encrypted using the proposed technique based on chaos and convolution neural network. Furthermore, multiple chaotic maps are incorporated to create a random number generator, and the generated random sequence is used for pixel permutation and substitution. In the second part of the proposed work, a new technique for pneumonia diagnosis using deep learning, in which X-ray images are used as a dataset, is proposed. Several physiological features such as cough, fever, chest pain, flu, low energy, sweating, shaking, chills, shortness of breath, fatigue, loss of appetite, and headache and statistical features such as entropy, correlation, contrast dissimilarity, etc., are extracted from the X-ray images for the pneumonia diagnosis. Moreover, machine learning algorithms such as support vector machines, decision trees, random forests, and naive Bayes are also implemented for the proposed model and compared with the proposed CNN-based model. Furthermore, to improve the CNN-based proposed model, transfer learning and fine tuning are also incorporated. It is found that CNN performs better than other machine learning algorithms as the accuracy of the proposed work when using naive Bayes and CNN is 89% and 97%, respectively, which is also greater than the average accuracy of the existing schemes, which is 90%. Further, K-fold analysis and voting techniques are also incorporated to improve the accuracy of the proposed model. Different metrics such as entropy, correlation, contrast, and energy are used to gauge the performance of the proposed encryption technology, while precision, recall, F1 score, and support are used to evaluate the effectiveness of the proposed machine learning-based model for pneumonia diagnosis. The entropy and correlation of the proposed work are 7.999 and 0.0001, respectively, which reflects that the proposed encryption algorithm offers a higher security of the digital data. Moreover, a detailed comparison with the existing work is also made and reveals that both the proposed models work better than the existing work

    Design of high gain base station antenna array for mm-wave cellular communication systems

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    Millimeter wave (mm-Wave) wireless communication systems require high gain antennas to overcome path loss effects and thereby enhance system coverage. This paper presents the design and analysis of an antenna array for high gain performance of future mm-wave 5G communication systems. The proposed antenna is based on planar microstrip technology and fabricated on 0.254 mm thick dielectric substrate (Rogers-5880) having a relative permittivity of 2.2 and loss tangent of 0.0009. The single radiating element used to construct the antenna array is a microstrip patch that has a configuration resembling a two-pronged fork. The single radiator has a realized gain of 7.6 dBi. To achieve the gain required by 5G base stations, a 64-element array antenna design is proposed which has a bore side gain of 21.2 dBi at 37.2 GHz. The 8 × 8, 8 × 16, and 8 × 32 antenna array designs described here were simulated and optimized using CST Microwave Studio, which is a 3D full-wave electromagnetic solver. The overall characteristics of the array in terms of reflection-coefficient and radiation patterns makes the proposed design suitable for mm-Wave 5G and other communication systems

    Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

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    Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

    High-Performance Multiple-Input Multiple-Output Antenna System For 5G Mobile Terminals

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    In this paper, the systematic design of a multiple antenna system for 5G smartphone operating at 3.5 GHz for multiple-input multiple-output (MIMO) operation in smartphones is proposed. The smartphone is preferred to be lightweight, thin, and attractive, and as a result metal casings have become popular. Using conventional antennas, such as a patch antenna, Inverted-F antennas, or monopole, in proximity to metal casing leads to decreasing its total efficiency and bandwidth. Therefore, a slot antenna embedded in the metal casing can be helpful, with good performance regarding bandwidth and total efficiency. The proposed multiple antenna system adopted the unit open-end slot antenna fed by Inverted-L microstrip with tuning stub. The measured S-parameters results agree fairly with the numerical results. It attains 200 MHz bandwidth at 3.5 GHz with ports isolation of (≤−13 dB) for any two antennas of the system. The influence of the customer’s hand for the proposed multiple antenna system is also considered, and the MIMO channel capacity is computed. The maximum achievable MIMO channel capacity based on the measured result is 31.25 bps/Hz and is about 2.7 times of 2 × 2 MIMO operation
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