Objective: To analyze the effect of combined extracorporeal shock wave and rehabilitation training treatment in patients with muscle articulation chronic pain (MACP). Methods: Ninety-seven MACP patients admitted to ou...Objective: To analyze the effect of combined extracorporeal shock wave and rehabilitation training treatment in patients with muscle articulation chronic pain (MACP). Methods: Ninety-seven MACP patients admitted to our hospital from September 2021 to September 2023 were randomly selected and were divided into Group A (control group, 46 cases, rehabilitation training treatment) and Group B (observation group, 51 cases, extracorporeal shock wave with rehabilitation training treatment), and outcomes of the two groups were compared. Results: The treatment efficiency, post-treatment clinical indexes (upper and lower limb function scores, activities of daily living (ADL) scores, visual analog scale (VAS) scores), and short-form 36 (SF-36) scores of Group B were better than those of Group A (P < 0.05). Conclusion: Combined extracorporeal shock wave and rehabilitation training treatment for MACP patients improved their limb function, daily activities, quality of life, and reduced pain.展开更多
In this paper, we introduce a novel scheme for the separate training of deep learning-based autoencoders used for Channel State Information (CSI) feedback. Our distinct training approach caters to multiple users and b...In this paper, we introduce a novel scheme for the separate training of deep learning-based autoencoders used for Channel State Information (CSI) feedback. Our distinct training approach caters to multiple users and base stations, enabling independent and individualized local training. This ensures the more secure processing of data and algorithms, different from the commonly adopted joint training method. To maintain comparable performance with joint training, we present two distinct training methods: separate training decoder and separate training encoder. It’s noteworthy that conducting separate training for the encoder can pose additional challenges, due to its responsibility in acquiring a compressed representation of underlying data features. This complexity makes accommodating multiple pre-trained decoders for just one encoder a demanding task. To overcome this, we design an adaptation layer architecture that effectively minimizes performance losses. Moreover, the flexible training strategy empowers users and base stations to seamlessly incorporate distinct encoder and decoder structures into the system, significantly amplifying the system’s scalability. .展开更多
Objective: To observe the effect of the joint injury of the distal radio-ulnar joint. Methods: 60 patients with Distal Radioulnar Joint (DRUJ) injury were divided into observation group and control group according to ...Objective: To observe the effect of the joint injury of the distal radio-ulnar joint. Methods: 60 patients with Distal Radioulnar Joint (DRUJ) injury were divided into observation group and control group according to random number method. 30 cases were included in each of the two groups.Before and after treatment in patients with Visual Analogue Scale (Visual Analogue Scale, VAS) score, forearm pronation and supination electromyographic activity, methods of electric integral value (integral electromyogram, iEMG) and Wrist in patients with self assessment Scale (Patient - Rated Wrist Evaluation, PRWE) score evaluation, comparison, and the clinical observation on diagnosis of disease and curative effect of traditional Chinese medicine standard (assessment process by blind method).Results: compared with the two groups before and after treatment, VAS score decreased, forearm pronation and postpronation activity increased, iEMG value increased, and PRWE scale score decreased (all P < 0.05), and the curative effect of the treatment group was better than that of the control group (P < 0.05). The total effective rate of the treatment group [93.3% (28/30)] was higher than that of the control group [50%(15/30), P < 0.05].Conclusion: the combined exercise training of muscle and bone setting technique can effectively alleviate the pain of patients with radial ulnar joint injury, improve the rotation of the forearm, increase the recruitment of the anterior rotatory muscle, and improve the wrist function of patients, and the effect is better than if combined with forearm support fixation.展开更多
Automatic speech recognition(ASR)systems have emerged as indispensable tools across a wide spectrum of applications,ranging from transcription services to voice-activated assistants.To enhance the performance of these...Automatic speech recognition(ASR)systems have emerged as indispensable tools across a wide spectrum of applications,ranging from transcription services to voice-activated assistants.To enhance the performance of these systems,it is important to deploy efficient models capable of adapting to diverse deployment conditions.In recent years,on-demand pruning methods have obtained significant attention within the ASR domain due to their adaptability in various deployment scenarios.However,these methods often confront substantial trade-offs,particularly in terms of unstable accuracy when reducing the model size.To address challenges,this study introduces two crucial empirical findings.Firstly,it proposes the incorporation of an online distillation mechanism during on-demand pruning training,which holds the promise of maintaining more consistent accuracy levels.Secondly,it proposes the utilization of the Mogrifier long short-term memory(LSTM)language model(LM),an advanced iteration of the conventional LSTM LM,as an effective alternative for pruning targets within the ASR framework.Through rigorous experimentation on the ASR system,employing the Mogrifier LSTM LM and training it using the suggested joint on-demand pruning and online distillation method,this study provides compelling evidence.The results exhibit that the proposed methods significantly outperform a benchmark model trained solely with on-demand pruning methods.Impressively,the proposed strategic configuration successfully reduces the parameter count by approximately 39%,all the while minimizing trade-offs.展开更多
文摘Objective: To analyze the effect of combined extracorporeal shock wave and rehabilitation training treatment in patients with muscle articulation chronic pain (MACP). Methods: Ninety-seven MACP patients admitted to our hospital from September 2021 to September 2023 were randomly selected and were divided into Group A (control group, 46 cases, rehabilitation training treatment) and Group B (observation group, 51 cases, extracorporeal shock wave with rehabilitation training treatment), and outcomes of the two groups were compared. Results: The treatment efficiency, post-treatment clinical indexes (upper and lower limb function scores, activities of daily living (ADL) scores, visual analog scale (VAS) scores), and short-form 36 (SF-36) scores of Group B were better than those of Group A (P < 0.05). Conclusion: Combined extracorporeal shock wave and rehabilitation training treatment for MACP patients improved their limb function, daily activities, quality of life, and reduced pain.
文摘In this paper, we introduce a novel scheme for the separate training of deep learning-based autoencoders used for Channel State Information (CSI) feedback. Our distinct training approach caters to multiple users and base stations, enabling independent and individualized local training. This ensures the more secure processing of data and algorithms, different from the commonly adopted joint training method. To maintain comparable performance with joint training, we present two distinct training methods: separate training decoder and separate training encoder. It’s noteworthy that conducting separate training for the encoder can pose additional challenges, due to its responsibility in acquiring a compressed representation of underlying data features. This complexity makes accommodating multiple pre-trained decoders for just one encoder a demanding task. To overcome this, we design an adaptation layer architecture that effectively minimizes performance losses. Moreover, the flexible training strategy empowers users and base stations to seamlessly incorporate distinct encoder and decoder structures into the system, significantly amplifying the system’s scalability. .
基金Key project of nature fund of anhui department of education(No.KJ2018a0273).
文摘Objective: To observe the effect of the joint injury of the distal radio-ulnar joint. Methods: 60 patients with Distal Radioulnar Joint (DRUJ) injury were divided into observation group and control group according to random number method. 30 cases were included in each of the two groups.Before and after treatment in patients with Visual Analogue Scale (Visual Analogue Scale, VAS) score, forearm pronation and supination electromyographic activity, methods of electric integral value (integral electromyogram, iEMG) and Wrist in patients with self assessment Scale (Patient - Rated Wrist Evaluation, PRWE) score evaluation, comparison, and the clinical observation on diagnosis of disease and curative effect of traditional Chinese medicine standard (assessment process by blind method).Results: compared with the two groups before and after treatment, VAS score decreased, forearm pronation and postpronation activity increased, iEMG value increased, and PRWE scale score decreased (all P < 0.05), and the curative effect of the treatment group was better than that of the control group (P < 0.05). The total effective rate of the treatment group [93.3% (28/30)] was higher than that of the control group [50%(15/30), P < 0.05].Conclusion: the combined exercise training of muscle and bone setting technique can effectively alleviate the pain of patients with radial ulnar joint injury, improve the rotation of the forearm, increase the recruitment of the anterior rotatory muscle, and improve the wrist function of patients, and the effect is better than if combined with forearm support fixation.
基金supported by Institute of Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2022-0-00377,Development of Intelligent Analysis and Classification Based Contents Class Categorization Technique to Prevent Imprudent Harmful Media Distribution).
文摘Automatic speech recognition(ASR)systems have emerged as indispensable tools across a wide spectrum of applications,ranging from transcription services to voice-activated assistants.To enhance the performance of these systems,it is important to deploy efficient models capable of adapting to diverse deployment conditions.In recent years,on-demand pruning methods have obtained significant attention within the ASR domain due to their adaptability in various deployment scenarios.However,these methods often confront substantial trade-offs,particularly in terms of unstable accuracy when reducing the model size.To address challenges,this study introduces two crucial empirical findings.Firstly,it proposes the incorporation of an online distillation mechanism during on-demand pruning training,which holds the promise of maintaining more consistent accuracy levels.Secondly,it proposes the utilization of the Mogrifier long short-term memory(LSTM)language model(LM),an advanced iteration of the conventional LSTM LM,as an effective alternative for pruning targets within the ASR framework.Through rigorous experimentation on the ASR system,employing the Mogrifier LSTM LM and training it using the suggested joint on-demand pruning and online distillation method,this study provides compelling evidence.The results exhibit that the proposed methods significantly outperform a benchmark model trained solely with on-demand pruning methods.Impressively,the proposed strategic configuration successfully reduces the parameter count by approximately 39%,all the while minimizing trade-offs.
