Accelerating and Compressing Deep Neural Networks for Massive MIMO CSI Feedback

The recent advances in machine learning and deep neural networks have made them attractive candidates for wireless communications functions such as channel estimation, decoding, and downlink channel state information (CSI) compression. However, most of these neural networks are large and inefficient making it a barrier for deployment in practical wireless systems that require low-latency and low memory footprints for individual network functions. To mitigate these limitations, we propose accelerated and compressed efficient neural networks for massive MIMO CSI feedback. Specifically, we have thoroughly investigated the adoption of network pruning, post-training dynamic range quantization, and weight clustering to optimize CSI feedback compression for massive MIMO systems. Furthermore, we have deployed the proposed model compression techniques on commodity hardware and demonstrated that in order to achieve inference gains, specialized libraries that accelerate computations for sparse neural networks are required. Our findings indicate that there is remarkable value in applying these model compression techniques and the proposed joint pruning and quantization approach reduced model size by 86.5% and inference time by 76.2% with minimal impact to model accuracy. These compression methods are crucial to pave the way for practical adoption and deployments of deep learning-based techniques in commercial wireless systems.Comment: IEEE ICC 2023 Conferenc

Empowering professional syndicates in Egypt to achieve good governance; An application to the Egyptian Medical Syndicate

In searching for a governance reform strategy, the size, the vital roles of professional syndicates and their impact on the whole society place them among our top priorities. According to both the old and the new Egyptian constitutions, the professional syndicates have the legal base to represent the different professions, defend rights and interests of their members, improve the quality of the offered services to the society, and share in creating policies and procedures related to syndicates\u27 members and their careers. The discrepancy between the proposed role of the professional syndicates and the reality motivated this research into the reasons behind their weaknesses and poor performance. Little recent analysis of Egypt\u27s syndicates could be found in the literature. Selecting the Egyptian Medical Syndicate (EMS) as a case study was invoked by its vital role in health system reform. The main research question is “To what extent do the governance structure and procedures of the Egyptian Medical Syndicate correspond to international good governance standards? The qualitative method was adopted in this research. The aspects of the governance of the Canadian Medical Association (CMA) were used as a guide to highlight what components and core compositions of the structures of the EMS should be examined in the governance process and how? In addition, two questionnaires were developed. The first one conducted to the members and the later to senior managers and Board members. The respondents answered these questionnaires through group interview for members and Individual In-Depth Interview for senior managers and Board members. The aim was to make sure through these instruments, it will be possible to assess to what extent the EMS covered the standards principles of good governance and illuminate the areas which need to be improved. The study targeted doctors in three Egyptian governorates (Cairo, Giza and Gharbia) and the sample included males and females from different ages and backgrounds. The research found that the current governance system and procedures are in a bad need to be reformed to be consistent with international good governance standards. The findings of the study illustrated that there is a crucial need to issue a new law and bylaw for the Egyptian Medical Syndicate. The elections’ system needs to be revised. There is a necessity to identify a clear vision and mission for the EMS, setting the long term objectives, consider the annual planning and evaluation for the programs and activities. The Board of Directors needs to enhance its leadership and strategic planning skills. The study also highlighted the importance of considering the new tools of communications such as emails, website and video conferences to share information, and to achieve greater connection, participation and involvements for the members of the EMS. This study open the door to further research with hope to develop a good model to evaluate the governance system in other professional syndicates, and it will be possible to apply the model with some adaptation to fit the specific features of each syndicate

Using Early Exits for Fast Inference in Automatic Modulation Classification

Automatic modulation classification (AMC) plays a critical role in wireless communications by autonomously classifying signals transmitted over the radio spectrum. Deep learning (DL) techniques are increasingly being used for AMC due to their ability to extract complex wireless signal features. However, DL models are computationally intensive and incur high inference latencies. This paper proposes the application of early exiting (EE) techniques for DL models used for AMC to accelerate inference. We present and analyze four early exiting architectures and a customized multi-branch training algorithm for this problem. Through extensive experimentation, we show that signals with moderate to high signal-to-noise ratios (SNRs) are easier to classify, do not require deep architectures, and can therefore leverage the proposed EE architectures. Our experimental results demonstrate that EE techniques can significantly reduce the inference speed of deep neural networks without sacrificing classification accuracy. We also thoroughly study the trade-off between classification accuracy and inference time when using these architectures. To the best of our knowledge, this work represents the first attempt to apply early exiting methods to AMC, providing a foundation for future research in this area

Perception of Biostatistics by Lebanese Medical Students: A Cross-Sectional Study

Background: Inadequate use of statistics in biomedical research might not only affect science but also harm human beings if applied in medical practice. Biostatistics is fundamental to improve understanding and appraising of evidence-based medicine (EBM); yet, it is still not well understood and appreciated by medical students. Therefore, early exposure of medical students and physicians-in-training to research tools including Biostatistics is of utmostimportance.Objective: The aim of this study is to determine the perception of Biostatistics by medical students at a private medical school in Beirut, Lebanon, and to identify its best implementation time in the medical curriculum.Methods: This is a cross-sectional study based on a self-administered questionnaire distributed among medical students in their pre-clerkship years (first three years of a 6-year program) who undertook Biostatistics. The assessment of perception was based on the 5-point Likert scale anchored by Strongly disagree = 1 and Strongly agree = 5 including 36 questions distributed into four domains to assess the course value, difficulty, behavioral, and expectations.Results: 186 of 269 students responded to the questionnaire, yielding a response rate of 69.14%. Around 60% of students declared that the knowledge gained from biostatistics courses is useful to their future career, and almost 70% understood the main concepts of biostatistics. 57.7% of students perceived that lack of practicing exercises might contribute to making the course more difficult. The mean score of domains was higher in females but did not significantly differ within the three academic years. Only 35.1% of the students positively perceived the importance of biostatistics modules, mostly third-year students.Conclusion: Although the majority of medical students perceived biostatistics modules negatively, they were aware of the relevance of biostatistics to their medical career and real-life health issues

達成可能及び残り一つを除いて達成可能な線量体積・平均線量制約に基づく計画のための強度変調放射線治療の最適化

We give a novel approach for obtaining an intensity-modulated radiation therapy (IMRT) optimization solution based on the idea of continuous dynamical methods. The proposed method, which is an iterative algorithm derived from the discretization of a continuous-time dynamical system, can handle not only dose-volume but also mean-dose constraints directly in IMRT treatment planning. A theoretical proof for the convergence to an equilibrium corresponding to the desired IMRT planning is given by using the Lyapunov stability theorem. By introducing the concept of “acceptable,” which means the existence of a nonempty set of beam weights satisfying the given dose-volume and mean-dose constraints, and by using the proposed method for an acceptable IMRT planning, one can resolve the issue that the objective and evaluation are different in the conventional planning process. Moreover, in the case where the target planning is totally unacceptable and partly acceptable except for one group of dose constraints, we give a procedure that enables us to obtain a nearly optimal solution close to the desired solution for unacceptable planning. The performance of the proposed approach for an acceptable or unacceptable planning is confirmed through numerical experiments simulating a clinical setup

Challenges and Opportunities of Health Care Supply Chain Management in the United States

This article explores current supply chain management challenges and initiatives and identifies problems that affect supply chain management success in the U.S. health-care industry. In addition, it investigates the impact of health care supply chain management (SCM) initiatives on the overall organizational effectiveness. The attitudinal results, as well as the performance results presented in this study support the claim of health care proponents that the SCM allows organizations to reduce cost, improve quality, and reduce cycle time, and leads to high performance

The ‘dinner date’ concept : reconciliating the dating and hospitality industries

Purpose: This research note argues that investigating the intersections between hospitality and speed dating events can yield practical implications for both industries. Hospitality professionals can gain valuable insights into how to enhance customer experiences by understanding the unique needs and expectations of individuals participating in dating events. Conversely, dating event organizers can draw upon the principles of hospitality to create more engaging and enjoyable experiences for their attendees, ultimately contributing to the success and longevity of such events. Methods: Adopting the User-Centred Design (UCD), which is structured around seven distinct phases including understand, observe, engage, define, ideate, prototype and test, and implement. Results: This study suggests a blueprint for the new concept of speed dating event. It proposes a methodology to develop a research agenda to generate strategies for implementing the “dinner date” concept. Implications: Developing aligning goals between hospitality and dating industries creates a valuable experience for their target audience, where food is presented as a soft management tool facilitating this relationship