[Objectives]To investigate the clinical efficacy of acupoint injection of nerve growth factors combined with task-oriented training for patients with post-stroke hemiplegic gait,and quantitatively evaluate the outcome...[Objectives]To investigate the clinical efficacy of acupoint injection of nerve growth factors combined with task-oriented training for patients with post-stroke hemiplegic gait,and quantitatively evaluate the outcomes using the Gait Watch analysis system.[Methods]A total of 90 patients with post-stroke hemiplegia,who were hospitalized at the Rehabilitation Center of Taihe Hospital between January 2023 and December 2023,were selected for this study.The participants were randomly assigned to three groups:the task-oriented rehabilitation training group(control group I,n=30),the ordinary acupuncture combined with task-oriented training group(control group II,n=30),and the acupoint injection combined with task-oriented training group(observation group,n=30).Each group underwent treatment for 4 weeks.The Gait Watch analysis system was employed to assess the spatiotemporal gait parameters of the patients prior to treatment,as well as 2 weeks post treatment and 4 weeks post treatment.The efficacy of the treatment was subsequently analyzed.[Results]After 4 weeks of treatment,the spatiotemporal gait parameters,specifically step length,step speed,step frequency,percentage of the standing phase,and percentage of the swinging phase,exhibited significant improvement in the observation group compared to those before treatment(P<0.05).Furthermore,the degree of improvement in the observation group was superior to that observed in both control group I and control group II,with the differences reaching statistical significance(P<0.05).[Conclusions]Acupoint injection combined with task-oriented training has been shown to significantly enhance gait function in patients with post-stroke hemiplegia.The Gait Watch analysis system offers an accurate and objective quantitative assessment,making it a valuable tool for clinical application and promotion.展开更多
Objective:To evaluate the effect of task-oriented training combined with a lower limb rehabilitation robot on improving motor function and ankle joint function in stroke patients with hemiplegia.Methods:Sixty-three st...Objective:To evaluate the effect of task-oriented training combined with a lower limb rehabilitation robot on improving motor function and ankle joint function in stroke patients with hemiplegia.Methods:Sixty-three stroke patients with hemiplegia admitted to our hospital from January 2022 to June 2024 were randomly divided into observation group(32 cases)and control group(31 cases)using the envelope method.The control group received task-oriented training,while the observation group received additional lower limb rehabilitation robot training.The motor function(Fugl-Meyer Assessment of Lower Extremity,FMA-LE)and ankle joint function(Active Dorsiflexion Range of Motion,DF AROM)were compared between the two groups.Results:After treatment,the levels of FMA-LE and DF AROM in both groups increased significantly,and the improvement in each index in the observation group was better than that in the control group(P<0.05).Conclusion:The combination of task-oriented training and lower limb rehabilitation robot training can more effectively improve the overall motor function of the lower limbs and the active dorsiflexion ability of the ankle joint in stroke patients with hemiplegia.展开更多
Objective: To explore the effect of lower limb rehabilitation robot combined with task-oriented training on stroke patients and its influence on KFAROM score. Methods: 100 stroke patients with hemiplegia admitted to o...Objective: To explore the effect of lower limb rehabilitation robot combined with task-oriented training on stroke patients and its influence on KFAROM score. Methods: 100 stroke patients with hemiplegia admitted to our hospital from January 2023 to December 2023 were randomly divided into two groups, the control group (50 cases) was given task-oriented training assisted by nurses, and the observation group (50 cases) was given lower limb rehabilitation robot with task-oriented training. Lower limb balance, lower limb muscle strength, motor function, ankle function, knee flexion range of motion and walking ability were observed. Results: After treatment, the scores of BBS, quadriceps femoris and hamstrings in the observation group were significantly higher than those in the control group (P Conclusion: In the clinical treatment of stroke patients, the combination of task-oriented training and lower limb rehabilitation robot can effectively improve the lower limb muscle strength, facilitate the recovery of balance function, and have a significant effect on the recovery of motor function, which can improve the walking ability of stroke patients and the range of motion of knee flexion, and achieve more ideal therapeutic effectiveness.展开更多
In the future development direction of the sixth generation(6G)mobile communication,several communication models are proposed to face the growing challenges of the task.The rapid development of artificial intelligence...In the future development direction of the sixth generation(6G)mobile communication,several communication models are proposed to face the growing challenges of the task.The rapid development of artificial intelligence(AI)foundation models provides significant support for efficient and intelligent communication interactions.In this paper,we propose an innovative semantic communication paradigm called task-oriented semantic communication system with foundation models.First,we segment the image by using task prompts based on the segment anything model(SAM)and contrastive language-image pretraining(CLIP).Meanwhile,we adopt Bezier curve to enhance the mask to improve the segmentation accuracy.Second,we have differentiated semantic compression and transmission approaches for segmented content.Third,we fuse different semantic information based on the conditional diffusion model to generate high-quality images that satisfy the users'specific task requirements.Finally,the experimental results show that the proposed system compresses the semantic information effectively and improves the robustness of semantic communication.展开更多
BACKGROUND Eighty percent of stroke patients develop upper limb dysfunction,especially hand dysfunction,which has a very slow recovery,resulting in economic burden to families and society.AIM To investigate the impact...BACKGROUND Eighty percent of stroke patients develop upper limb dysfunction,especially hand dysfunction,which has a very slow recovery,resulting in economic burden to families and society.AIM To investigate the impact of task-oriented training based on acupuncture therapy on upper extremity function in patients with early stroke.METHODS Patients with early stroke hemiplegia who visited our hospital between January 2021 and October 2022 were divided into a control group and an observation group,each with 50 cases.The control group underwent head acupuncture plus routine upper limb rehabilitation training(acupuncture therapy).In addition to acupuncture and rehabilitation,the observation group underwent upper limb task-oriented training(30 min).Each group underwent treatment 5 d/wk for 4 wk.Upper extremity function was assessed in both groups using the Fugl-Meyer Assessment-Upper Extremity(FMA-UE),Wolf Motor Function Rating Scale(WMFT),modified Barthel Index(MBI),and Canadian Occupational Performance Measure(COPM).Quality of life was evaluated using the Short-Form 36-Item Health Survey(SF-36).Clinical efficacy of the interventions was also evaluated.RESULTS Before intervention,no significant differences were observed in the FMA-UE,MBI,and WMFT scores between the two groups(P>0.05).After intervention,the FMA-UE,WMFT,MBI,COPM-Functional Mobility and Satisfaction,and SF-36 scores increased in both groups(P<0.05),with even higher scores in the observation group(P<0.05).The observation group also obtained a higher total effective rate than the control group(P<0.05).CONCLUSION Task-oriented training based on acupuncture rehabilitation significantly enhanced upper extremity mobility,quality of life,and clinical efficacy in patients with early stroke.展开更多
The rapid expansion of enterprises makes product collaborative design （PCD） a critical issue under the distributed heterogeneous environment, but as the collaborative task of large-scale network becomes more complic...The rapid expansion of enterprises makes product collaborative design （PCD） a critical issue under the distributed heterogeneous environment, but as the collaborative task of large-scale network becomes more complicated, neither unified task decomposition and allocation methodology nor Agent-based network management platform can satisfy the increasing demands. In this paper, to meet requirements of PCD for distributed product development, a collaborative design mechanism based on the thought of modularity and the Agent technology is presented. First, the top-down 4-tier process model based on task-oriented modular and Agent is constructed for PCD after analyzing the mapping relationships between requirements and functions in the collaborative design. Second, on basis of sub-task decomposition for PCD based on a mixed method, the mathematic model of task-oriented modular based on multi-objective optimization is established to maximize the module cohesion degree and minimize the module coupling degree, while considering the module executable degree as a restriction. The mathematic model is optimized and simulated by the modified PSO, and the decomposed modules are obtained. Finally, the Agent structure model for collaborative design is put forward, and the optimism matching Agents are selected by using similarity algorithm to implement different task-modules by the integrated reasoning and decision-making mechanism with the behavioral model of collaborative design Agents. With the results of experimental studies for automobile collaborative design, the feasibility and efficiency of this methodology of task-oriented modular and Agent-based collaborative design in the distributed heterogeneous environment are verified. On this basis, an integrative automobile collaborative R＆D platform is developed. This research provides an effective platform for automobile manufacturing enterprises to achieve PCD, and helps to promote product numeralization collaborative R＆D and management development.展开更多
This paper concerns itself with a task-oriented approach to the pre-service teacher education in the Classroom of English Teaching Methodology （ETM）. We attempt to use an explicit theoretic framework to guide the pr...This paper concerns itself with a task-oriented approach to the pre-service teacher education in the Classroom of English Teaching Methodology （ETM）. We attempt to use an explicit theoretic framework to guide the practice of ETM classroom in teacher education. The basic assumption is that we can use methodology which we use in teaching language, and apply those techniques and methods to train student teachers. By this approach the student teachers can adopt a research orientation to their own classrooms and their own teaching, an inquiry-based and discovery-oriented approach to learning is greatly emphasized, and they also can form the habit of generating theories and hypotheses and reflecting critically on teaching.展开更多
Consistency identification in task-oriented dialogue(CI-ToD)can prevent inconsistent dialogue response generation,which has recently emerged as an important and growing research area.This paper takes the first step to...Consistency identification in task-oriented dialogue(CI-ToD)can prevent inconsistent dialogue response generation,which has recently emerged as an important and growing research area.This paper takes the first step to explore a pre-training paradigm for CI-ToD.Nevertheless,pre-training for CI-ToD is non-trivial because it requires a large amount of multi-turn KB-grounded dialogues,which are extremely hard to collect.To alleviate the data scarcity problem for pre-training,we introduce a modularized pre-training framework(MPFToD),which is capable of utilizing large amounts of KB-free dialogues.Specifically,such modularization allows us to decouple CI-ToD into three sub-modules and propose three pre-training tasks including(i)query response matching pre-training;(ii)dialogue history consistent identification pre-training;and(iii)KB mask language modeling to enhance different abilities of CI-ToD model.As different sub-tasks are solved separately,MPFToD can learn from large amounts of KB-free dialogues for different modules,which are much easier to obtain.Results on the CI-ToD benchmark show that MPFToD pushes the state-of-the-art performance from 56.3%to 61.0%.Furthermore,we show its transferability with promising performance on other downstream tasks(i.e.,dialog act recognition,sentiment classification and table fact checking).展开更多
Due to the significance and value in human-computer interaction and natural language processing,task-oriented dialog systems are attracting more and more attention in both academic and industrial communities.In this p...Due to the significance and value in human-computer interaction and natural language processing,task-oriented dialog systems are attracting more and more attention in both academic and industrial communities.In this paper,we survey recent advances and challenges in task-oriented dialog systems.We also discuss three critical topics for task-oriented dialog systems:(1)improving data efficiency to facilitate dialog modeling in low-resource settings,(2)modeling multi-turn dynamics for dialog policy learning to achieve better task-completion performance,and(3)integrating domain ontology knowledge into the dialog model.Besides,we review the recent progresses in dialog evaluation and some widely-used corpora.We believe that this survey,though incomplete,can shed a light on future research in task-oriented dialog systems.展开更多
Dialogue policy learning(DPL)is a key component in a task-oriented dialogue(TOD)system.Its goal is to decide the next action of the dialogue system,given the dialogue state at each turn based on a learned dialogue pol...Dialogue policy learning(DPL)is a key component in a task-oriented dialogue(TOD)system.Its goal is to decide the next action of the dialogue system,given the dialogue state at each turn based on a learned dialogue policy.Reinforcement learning(RL)is widely used to optimize this dialogue policy.In the learning process,the user is regarded as the environment and the system as the agent.In this paper,we present an overview of the recent advances and challenges in dialogue policy from the perspective of RL.More specifically,we identify the problems and summarize corresponding solutions for RL-based dialogue policy learning.In addition,we provide a comprehensive survey of applying RL to DPL by categorizing recent methods into five basic elements in RL.We believe this survey can shed light on future research in DPL.展开更多
In industrial manufacturing,the deployment of dual-arm robots in assembly tasks has become a trend.However,making the dual-arm robots more intelligent in such applications is still an open,challenging issue.This paper...In industrial manufacturing,the deployment of dual-arm robots in assembly tasks has become a trend.However,making the dual-arm robots more intelligent in such applications is still an open,challenging issue.This paper proposes a novel framework that combines task-oriented motion planning with visual perception to facilitate robot deployment from perception to execution and finish assembly problems by using dual-arm robots.In this framework,visual perception is first employed to track the effects of the robot behaviors and observe states of the workpieces,where the performance of tasks can be abstracted as a high-level state for intelligent reasoning.The assembly task and manipulation sequences can be obtained by analyzing and reasoning the state transition trajectory of the environment as well as the workpieces.Next,the corresponding assembly manipulation can be generated and parameterized according to the differences between adjacent states by combining with the prebuilt knowledge of the scenarios.Experiments are set up with a dual-arm robotic system(ABB YuMi and an RGB-D camera)to validate the proposed framework.Experimental results demonstrate the effectiveness of the proposed framework and the promising value of its practical application.展开更多
Cooperative planning is one of the critical problems in the field of multi-agent system gaming.This work focuses on cooperative planning when each agent has only a local observation range and local communication.We pr...Cooperative planning is one of the critical problems in the field of multi-agent system gaming.This work focuses on cooperative planning when each agent has only a local observation range and local communication.We propose a novel cooperative planning architecture that combines a graph neural network with a task-oriented knowledge fusion sampling method.Two main contributions of this paper are based on the comparisons with previous work:(1)we realize feasible and dynamic adjacent information fusion using GraphSAGE(i.e.,Graph SAmple and aggreGatE),which is the first time this method has been used to deal with the cooperative planning problem,and(2)a task-oriented sampling method is proposed to aggregate the available knowledge from a particular orientation,to obtain an effective and stable training process in our model.Experimental results demonstrate the good performance of our proposed method.展开更多
This paper focuses on end-to-end task-oriented dialogue systems,which jointly handle dialogue state tracking(DST)and response generation.Traditional methods usually adopt a supervised paradigm to learn DST from a manu...This paper focuses on end-to-end task-oriented dialogue systems,which jointly handle dialogue state tracking(DST)and response generation.Traditional methods usually adopt a supervised paradigm to learn DST from a manually labeled corpus.However,the annotation of the corpus is costly,time-consuming,and cannot cover a wide range of domains in the real world.To solve this problem,we propose a multi-span prediction network(MSPN)that performs unsupervised DST for end-to-end task-oriented dialogue.Specifically,MSPN contains a novel split-merge copy mechanism that captures long-term dependencies in dialogues to automatically extract multiple text spans as keywords.Based on these keywords,MSPN uses a semantic distance based clustering approach to obtain the values of each slot.In addition,we propose an ontology-based reinforcement learning approach,which employs the values of each slot to train MSPN to generate relevant values.Experimental results on single-domain and multi-domain task-oriented dialogue datasets show that MSPN achieves state-of-the-art performance with significant improvements.Besides,we construct a new Chinese dialogue dataset MeDial in the low-resource medical domain,which further demonstrates the adaptability of MSPN.展开更多
After spinal cord injury,impairment of the sensorimotor circuit can lead to dysfunction in the motor,sensory,proprioceptive,and autonomic nervous systems.Functional recovery is often hindered by constraints on the tim...After spinal cord injury,impairment of the sensorimotor circuit can lead to dysfunction in the motor,sensory,proprioceptive,and autonomic nervous systems.Functional recovery is often hindered by constraints on the timing of interventions,combined with the limitations of current methods.To address these challenges,various techniques have been developed to aid in the repair and reconstruction of neural circuits at different stages of injury.Notably,neuromodulation has garnered considerable attention for its potential to enhance nerve regeneration,provide neuroprotection,restore neurons,and regulate the neural reorganization of circuits within the cerebral cortex and corticospinal tract.To improve the effectiveness of these interventions,the implementation of multitarget early interventional neuromodulation strategies,such as electrical and magnetic stimulation,is recommended to enhance functional recovery across different phases of nerve injury.This review concisely outlines the challenges encountered following spinal cord injury,synthesizes existing neurostimulation techniques while emphasizing neuroprotection,repair,and regeneration of impaired connections,and advocates for multi-targeted,task-oriented,and timely interventions.展开更多
In task-oriented dialogue systems, intent, emotion, and actions are crucial elements of user activity. Analyzing the relationships among these elements to control and manage task-oriented dialogue systems is a challen...In task-oriented dialogue systems, intent, emotion, and actions are crucial elements of user activity. Analyzing the relationships among these elements to control and manage task-oriented dialogue systems is a challenging task. However, previous work has primarily focused on the independent recognition of user intent and emotion, making it difficult to simultaneously track both aspects in the dialogue tracking module and to effectively utilize user emotions in subsequent dialogue strategies. We propose a Multi-Head Encoder Shared Model (MESM) that dynamically integrates features from emotion and intent encoders through a feature fusioner. Addressing the scarcity of datasets containing both emotion and intent labels, we designed a multi-dataset learning approach enabling the model to generate dialogue summaries encompassing both user intent and emotion. Experiments conducted on the MultiWoZ and MELD datasets demonstrate that our model effectively captures user intent and emotion, achieving extremely competitive results in dialogue state tracking tasks.展开更多
Objective: The aim of this article is to reflect on the role of theater nurses in a multidisciplinary team, understand the factors that have influenced theater nurses' practice, and improve the authors' clinic...Objective: The aim of this article is to reflect on the role of theater nurses in a multidisciplinary team, understand the factors that have influenced theater nurses' practice, and improve the authors' clinical practice ultimately.Methods: The author used Smyth's model to guide the process of reflection on the practice issue. Critical reflection, critical emancipatory theory, reflexivity, and critical social theory were used to help the author analyze the factors that have affected theater nurses' practice in the organization.Results: There are gaps between the espoused and enacted theories. A theater nurse's practice is determined by multiple factors, such as political, structural, social, historical, cultural issues, and so on. The hierarchy of the health context could hinder possible changes in theater nurses' practice. To better understand our practice and implement transformation, we should shape a supportive environment,bear in mind the practice motto of "patient-centered" care, and improve our knowledge and reflection skills.Conclusions: Reflection plays a significant role in the advancing of practice among theater nurses and needs to be combined with clinical practice. To provide the best service of care to perioperative patients, a theater nurse should have an insightful understanding of the factors that have influenced her/his behaviors historically, socially, and culturally. By improving their critical reflection skills,practitioners could gain knowledge from experience.展开更多
The broad objective of this study was to establish the moderating effect of corporate culture on the relationship between intellectual capital and organizational performance of firms listed on Nairobi Securities Excha...The broad objective of this study was to establish the moderating effect of corporate culture on the relationship between intellectual capital and organizational performance of firms listed on Nairobi Securities Exchange. The review of literature provided conceptual and empirical gaps that formed the basis of the conceptual hypotheses. Two hypotheses were deduced from general objective： Intellectual capital has a significant influence on corporate performance; corporate culture moderates the relationship between intellectual capital and corporate performance. A cross-section research design was adopted. A survey questionnaire was the main tool of data collection and was distributed to the 50 heads of human resource departments in the different firms＇ period covering four financial years from 2009 to 2012. The study also utilized secondary data obtained from Capital Market Authority Statistical bulletins and Nairobi Securities Exchange Handbook 2012-2013 to collect data on financial performance （ROA, ROE, and Dividend Yield）. Data were tested for reliability results showing that study dimensions were reliable, apart from task-oriented culture that had a Cronbach alpha of 0.262, thus being not considered for further analysis; thus the study relied on employee-oriented culture as a measure of corporate culture. The hypotheses were tested using multiple regression analysis and hierarchical regression respectively. Multiple regression analysis showed that intellectual capital had a significant influence on non-financial performance and no significant influence on financial measures of performance （ROA, ROE, and Dividend Yield）. Test for moderation showed that the interaction term was not significant and thus, employee-oriented culture did not moderate the relationship between intellectual capital and corporate performance. The study demonstrates importance of the influence of intellectual capital on non-financial performance of firms listed on Nairobi Securities Exchange. The results show that interplay among human capital, social capital, and organization capital is important for firms listed on Nairobi Securities Exchange and that the firms should nurture the employees into sharing their knowledge by creating internal and external networks and also creating support system within the organization to retain the knowledge.展开更多
With the advent of the Internet of Everything(IoE),the concept of fully interconnected systems has become a reality,and the need for seamless communication and interoperability among different industrial systems has b...With the advent of the Internet of Everything(IoE),the concept of fully interconnected systems has become a reality,and the need for seamless communication and interoperability among different industrial systems has become more pressing than ever before.To address the challenges posed by massive data traffic,we demonstrate the potentials of semantic information processing in industrial manufacturing processes and then propose a brief framework of semantic processing and communication system for industrial network.In particular,the scheme is featured with task-orientation and collaborative processing.To illustrate its applicability,we provide examples of time series and images,as typical industrial data sources,for practical tasks,such as lifecycle estimation and surface defect detection.Simulation results show that semantic information processing achieves a more efficient way of information processing and exchanging,compared to conventional methods,which is crucial for handling the demands of future interconnected industrial networks.展开更多
Risk communication is a significant challenge in risk management.It serves different purposes;an important one is to improve the public risk awareness and mitigation.Because of the strong spatio-temporal component of ...Risk communication is a significant challenge in risk management.It serves different purposes;an important one is to improve the public risk awareness and mitigation.Because of the strong spatio-temporal component of natural hazards,maps can play a decisive role in communicating risk information.The application and design of maps for risk communication especially to the public has not been investigated comprehensively.Specific constraints and challenges of risk communication have not been considered systematically in the map design process so far.This study aims at developing a frame for the application and design of interactive risk and hazard maps for the public which is based on the specific constraints and challenges of risk communication.In a literature review it introduces concepts and methods from social sciences and psychology,which have been assessed as important for communicating risk information.The concepts and methods are adapted to map-mediated risk communication according to the approaches of Activity Theory.Communication objectives and tasks which are essential to improve risk mitigation are identified and geovisualization methods for information presentation are related according to the degree which they are able to serve them.Based on this,some principles for map-based risk communication are established.展开更多
The human-computer dialogue has recently attracted extensive attention from both academia and industry as an important branch in the field of artificial intelligence(AI).However,there are few studies on the evaluation...The human-computer dialogue has recently attracted extensive attention from both academia and industry as an important branch in the field of artificial intelligence(AI).However,there are few studies on the evaluation of large-scale Chinese human-computer dialogue systems.In this paper,we introduce the Second Evaluation of Chinese Human-Computer Dialogue Technology,which focuses on the identification of a user’s intents and intelligent processing of intent words.The Evaluation consists of user intent classification(Task 1)and online testing of task-oriented dialogues(Task 2),the data sets of which are provided by iFLYTEK Corporation.The evaluation tasks and data sets are introduced in detail,and meanwhile,the evaluation results and the existing problems in the evaluation are discussed.展开更多
基金Supported by Hospital-level Project of Shiyan Taihe Hospital(2019JJXM117).
文摘[Objectives]To investigate the clinical efficacy of acupoint injection of nerve growth factors combined with task-oriented training for patients with post-stroke hemiplegic gait,and quantitatively evaluate the outcomes using the Gait Watch analysis system.[Methods]A total of 90 patients with post-stroke hemiplegia,who were hospitalized at the Rehabilitation Center of Taihe Hospital between January 2023 and December 2023,were selected for this study.The participants were randomly assigned to three groups:the task-oriented rehabilitation training group(control group I,n=30),the ordinary acupuncture combined with task-oriented training group(control group II,n=30),and the acupoint injection combined with task-oriented training group(observation group,n=30).Each group underwent treatment for 4 weeks.The Gait Watch analysis system was employed to assess the spatiotemporal gait parameters of the patients prior to treatment,as well as 2 weeks post treatment and 4 weeks post treatment.The efficacy of the treatment was subsequently analyzed.[Results]After 4 weeks of treatment,the spatiotemporal gait parameters,specifically step length,step speed,step frequency,percentage of the standing phase,and percentage of the swinging phase,exhibited significant improvement in the observation group compared to those before treatment(P<0.05).Furthermore,the degree of improvement in the observation group was superior to that observed in both control group I and control group II,with the differences reaching statistical significance(P<0.05).[Conclusions]Acupoint injection combined with task-oriented training has been shown to significantly enhance gait function in patients with post-stroke hemiplegia.The Gait Watch analysis system offers an accurate and objective quantitative assessment,making it a valuable tool for clinical application and promotion.
文摘Objective:To evaluate the effect of task-oriented training combined with a lower limb rehabilitation robot on improving motor function and ankle joint function in stroke patients with hemiplegia.Methods:Sixty-three stroke patients with hemiplegia admitted to our hospital from January 2022 to June 2024 were randomly divided into observation group(32 cases)and control group(31 cases)using the envelope method.The control group received task-oriented training,while the observation group received additional lower limb rehabilitation robot training.The motor function(Fugl-Meyer Assessment of Lower Extremity,FMA-LE)and ankle joint function(Active Dorsiflexion Range of Motion,DF AROM)were compared between the two groups.Results:After treatment,the levels of FMA-LE and DF AROM in both groups increased significantly,and the improvement in each index in the observation group was better than that in the control group(P<0.05).Conclusion:The combination of task-oriented training and lower limb rehabilitation robot training can more effectively improve the overall motor function of the lower limbs and the active dorsiflexion ability of the ankle joint in stroke patients with hemiplegia.
文摘Objective: To explore the effect of lower limb rehabilitation robot combined with task-oriented training on stroke patients and its influence on KFAROM score. Methods: 100 stroke patients with hemiplegia admitted to our hospital from January 2023 to December 2023 were randomly divided into two groups, the control group (50 cases) was given task-oriented training assisted by nurses, and the observation group (50 cases) was given lower limb rehabilitation robot with task-oriented training. Lower limb balance, lower limb muscle strength, motor function, ankle function, knee flexion range of motion and walking ability were observed. Results: After treatment, the scores of BBS, quadriceps femoris and hamstrings in the observation group were significantly higher than those in the control group (P Conclusion: In the clinical treatment of stroke patients, the combination of task-oriented training and lower limb rehabilitation robot can effectively improve the lower limb muscle strength, facilitate the recovery of balance function, and have a significant effect on the recovery of motor function, which can improve the walking ability of stroke patients and the range of motion of knee flexion, and achieve more ideal therapeutic effectiveness.
基金supported in part by the National Natural Science Foundation of China under Grant(62001246,62231017,62201277,62071255)the Natural Science Foundation of Jiangsu Province under Grant BK20220390+3 种基金Key R and D Program of Jiangsu Province Key project and topics under Grant(BE2021095,BE2023035)the Natural Science Research Startup Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(Grant No.NY221011)National Science Foundation of Xiamen,China(No.3502Z202372013)Open Project of the Key Laboratory of Underwater Acoustic Communication and Marine Information Technology(Xiamen University)of the Ministry of Education,China(No.UAC202304)。
文摘In the future development direction of the sixth generation(6G)mobile communication,several communication models are proposed to face the growing challenges of the task.The rapid development of artificial intelligence(AI)foundation models provides significant support for efficient and intelligent communication interactions.In this paper,we propose an innovative semantic communication paradigm called task-oriented semantic communication system with foundation models.First,we segment the image by using task prompts based on the segment anything model(SAM)and contrastive language-image pretraining(CLIP).Meanwhile,we adopt Bezier curve to enhance the mask to improve the segmentation accuracy.Second,we have differentiated semantic compression and transmission approaches for segmented content.Third,we fuse different semantic information based on the conditional diffusion model to generate high-quality images that satisfy the users'specific task requirements.Finally,the experimental results show that the proposed system compresses the semantic information effectively and improves the robustness of semantic communication.
文摘BACKGROUND Eighty percent of stroke patients develop upper limb dysfunction,especially hand dysfunction,which has a very slow recovery,resulting in economic burden to families and society.AIM To investigate the impact of task-oriented training based on acupuncture therapy on upper extremity function in patients with early stroke.METHODS Patients with early stroke hemiplegia who visited our hospital between January 2021 and October 2022 were divided into a control group and an observation group,each with 50 cases.The control group underwent head acupuncture plus routine upper limb rehabilitation training(acupuncture therapy).In addition to acupuncture and rehabilitation,the observation group underwent upper limb task-oriented training(30 min).Each group underwent treatment 5 d/wk for 4 wk.Upper extremity function was assessed in both groups using the Fugl-Meyer Assessment-Upper Extremity(FMA-UE),Wolf Motor Function Rating Scale(WMFT),modified Barthel Index(MBI),and Canadian Occupational Performance Measure(COPM).Quality of life was evaluated using the Short-Form 36-Item Health Survey(SF-36).Clinical efficacy of the interventions was also evaluated.RESULTS Before intervention,no significant differences were observed in the FMA-UE,MBI,and WMFT scores between the two groups(P>0.05).After intervention,the FMA-UE,WMFT,MBI,COPM-Functional Mobility and Satisfaction,and SF-36 scores increased in both groups(P<0.05),with even higher scores in the observation group(P<0.05).The observation group also obtained a higher total effective rate than the control group(P<0.05).CONCLUSION Task-oriented training based on acupuncture rehabilitation significantly enhanced upper extremity mobility,quality of life,and clinical efficacy in patients with early stroke.
基金Supported by National Science and Technology Major Project of China(Grant No.2009ZX04014-103)PhD Programs Foundation of Ministry of Education of China(Grant No.20100072110038)+1 种基金National Natural Science Foundation of China(Grant Nos.61075064,61034004,61005090)Program for New Century Excellent Talents in University of Ministry of Education of China(Grant No.NECT-10-0633)
文摘The rapid expansion of enterprises makes product collaborative design （PCD） a critical issue under the distributed heterogeneous environment, but as the collaborative task of large-scale network becomes more complicated, neither unified task decomposition and allocation methodology nor Agent-based network management platform can satisfy the increasing demands. In this paper, to meet requirements of PCD for distributed product development, a collaborative design mechanism based on the thought of modularity and the Agent technology is presented. First, the top-down 4-tier process model based on task-oriented modular and Agent is constructed for PCD after analyzing the mapping relationships between requirements and functions in the collaborative design. Second, on basis of sub-task decomposition for PCD based on a mixed method, the mathematic model of task-oriented modular based on multi-objective optimization is established to maximize the module cohesion degree and minimize the module coupling degree, while considering the module executable degree as a restriction. The mathematic model is optimized and simulated by the modified PSO, and the decomposed modules are obtained. Finally, the Agent structure model for collaborative design is put forward, and the optimism matching Agents are selected by using similarity algorithm to implement different task-modules by the integrated reasoning and decision-making mechanism with the behavioral model of collaborative design Agents. With the results of experimental studies for automobile collaborative design, the feasibility and efficiency of this methodology of task-oriented modular and Agent-based collaborative design in the distributed heterogeneous environment are verified. On this basis, an integrative automobile collaborative R＆D platform is developed. This research provides an effective platform for automobile manufacturing enterprises to achieve PCD, and helps to promote product numeralization collaborative R＆D and management development.
文摘This paper concerns itself with a task-oriented approach to the pre-service teacher education in the Classroom of English Teaching Methodology （ETM）. We attempt to use an explicit theoretic framework to guide the practice of ETM classroom in teacher education. The basic assumption is that we can use methodology which we use in teaching language, and apply those techniques and methods to train student teachers. By this approach the student teachers can adopt a research orientation to their own classrooms and their own teaching, an inquiry-based and discovery-oriented approach to learning is greatly emphasized, and they also can form the habit of generating theories and hypotheses and reflecting critically on teaching.
基金supported by the National Natural Science Foundation of China(NSFC)(Grant Nos.62306342,62176076)the Excellent Young Scientists Fund in Hunan Province(2024JJ4070)+3 种基金supported by the Natural Science Foundation of Guangdong(2023A1515012922)Shenzhen Foundational Research Funding(JCYJ20220818102415032)The Major Key Project of PCL(PCL2023A09)Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies(2022B1212010005k).
文摘Consistency identification in task-oriented dialogue(CI-ToD)can prevent inconsistent dialogue response generation,which has recently emerged as an important and growing research area.This paper takes the first step to explore a pre-training paradigm for CI-ToD.Nevertheless,pre-training for CI-ToD is non-trivial because it requires a large amount of multi-turn KB-grounded dialogues,which are extremely hard to collect.To alleviate the data scarcity problem for pre-training,we introduce a modularized pre-training framework(MPFToD),which is capable of utilizing large amounts of KB-free dialogues.Specifically,such modularization allows us to decouple CI-ToD into three sub-modules and propose three pre-training tasks including(i)query response matching pre-training;(ii)dialogue history consistent identification pre-training;and(iii)KB mask language modeling to enhance different abilities of CI-ToD model.As different sub-tasks are solved separately,MPFToD can learn from large amounts of KB-free dialogues for different modules,which are much easier to obtain.Results on the CI-ToD benchmark show that MPFToD pushes the state-of-the-art performance from 56.3%to 61.0%.Furthermore,we show its transferability with promising performance on other downstream tasks(i.e.,dialog act recognition,sentiment classification and table fact checking).
基金the National Natural Science Foundation of China(Grant Nos.61936010 and 61876096)the National Key R&D Program of China(Grant No.2018YFC0830200)。
文摘Due to the significance and value in human-computer interaction and natural language processing,task-oriented dialog systems are attracting more and more attention in both academic and industrial communities.In this paper,we survey recent advances and challenges in task-oriented dialog systems.We also discuss three critical topics for task-oriented dialog systems:(1)improving data efficiency to facilitate dialog modeling in low-resource settings,(2)modeling multi-turn dynamics for dialog policy learning to achieve better task-completion performance,and(3)integrating domain ontology knowledge into the dialog model.Besides,we review the recent progresses in dialog evaluation and some widely-used corpora.We believe that this survey,though incomplete,can shed a light on future research in task-oriented dialog systems.
基金Innovation and Technology Fund(ITF),Government of the Hong Kong Special Administrative Region(HKSAR),China(No.PRP-054-21FX).
文摘Dialogue policy learning(DPL)is a key component in a task-oriented dialogue(TOD)system.Its goal is to decide the next action of the dialogue system,given the dialogue state at each turn based on a learned dialogue policy.Reinforcement learning(RL)is widely used to optimize this dialogue policy.In the learning process,the user is regarded as the environment and the system as the agent.In this paper,we present an overview of the recent advances and challenges in dialogue policy from the perspective of RL.More specifically,we identify the problems and summarize corresponding solutions for RL-based dialogue policy learning.In addition,we provide a comprehensive survey of applying RL to DPL by categorizing recent methods into five basic elements in RL.We believe this survey can shed light on future research in DPL.
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.61873308,61503076,and 61175113)the Natural Science Foundation of Jiangsu Province(Grant No.BK20150624)the Fundamental Research Funds for the Central Universities(Grant No.202008003).
文摘In industrial manufacturing,the deployment of dual-arm robots in assembly tasks has become a trend.However,making the dual-arm robots more intelligent in such applications is still an open,challenging issue.This paper proposes a novel framework that combines task-oriented motion planning with visual perception to facilitate robot deployment from perception to execution and finish assembly problems by using dual-arm robots.In this framework,visual perception is first employed to track the effects of the robot behaviors and observe states of the workpieces,where the performance of tasks can be abstracted as a high-level state for intelligent reasoning.The assembly task and manipulation sequences can be obtained by analyzing and reasoning the state transition trajectory of the environment as well as the workpieces.Next,the corresponding assembly manipulation can be generated and parameterized according to the differences between adjacent states by combining with the prebuilt knowledge of the scenarios.Experiments are set up with a dual-arm robotic system(ABB YuMi and an RGB-D camera)to validate the proposed framework.Experimental results demonstrate the effectiveness of the proposed framework and the promising value of its practical application.
基金Project supported by the National Natural Science Foundation。
文摘Cooperative planning is one of the critical problems in the field of multi-agent system gaming.This work focuses on cooperative planning when each agent has only a local observation range and local communication.We propose a novel cooperative planning architecture that combines a graph neural network with a task-oriented knowledge fusion sampling method.Two main contributions of this paper are based on the comparisons with previous work:(1)we realize feasible and dynamic adjacent information fusion using GraphSAGE(i.e.,Graph SAmple and aggreGatE),which is the first time this method has been used to deal with the cooperative planning problem,and(2)a task-oriented sampling method is proposed to aggregate the available knowledge from a particular orientation,to obtain an effective and stable training process in our model.Experimental results demonstrate the good performance of our proposed method.
基金supported by the National Key Research and Development Program of China under Grant No.2020AAA0106400the National Natural Science Foundation of China under Grant Nos.61922085 and 61976211+2 种基金the Independent Research Project of National Laboratory of Pattern Recognition under Grant No.Z-2018013the Key Research Program of Chinese Academy of Sciences(CAS)under Grant No.ZDBS-SSW-JSC006the Youth Innovation Promotion Association CAS under Grant No.201912.
文摘This paper focuses on end-to-end task-oriented dialogue systems,which jointly handle dialogue state tracking(DST)and response generation.Traditional methods usually adopt a supervised paradigm to learn DST from a manually labeled corpus.However,the annotation of the corpus is costly,time-consuming,and cannot cover a wide range of domains in the real world.To solve this problem,we propose a multi-span prediction network(MSPN)that performs unsupervised DST for end-to-end task-oriented dialogue.Specifically,MSPN contains a novel split-merge copy mechanism that captures long-term dependencies in dialogues to automatically extract multiple text spans as keywords.Based on these keywords,MSPN uses a semantic distance based clustering approach to obtain the values of each slot.In addition,we propose an ontology-based reinforcement learning approach,which employs the values of each slot to train MSPN to generate relevant values.Experimental results on single-domain and multi-domain task-oriented dialogue datasets show that MSPN achieves state-of-the-art performance with significant improvements.Besides,we construct a new Chinese dialogue dataset MeDial in the low-resource medical domain,which further demonstrates the adaptability of MSPN.
基金supported by the National Key Research and Development Program of China,No.2023YFC3603705(to DX)the National Natural Science Foundation of China,No.82302866(to YZ).
文摘After spinal cord injury,impairment of the sensorimotor circuit can lead to dysfunction in the motor,sensory,proprioceptive,and autonomic nervous systems.Functional recovery is often hindered by constraints on the timing of interventions,combined with the limitations of current methods.To address these challenges,various techniques have been developed to aid in the repair and reconstruction of neural circuits at different stages of injury.Notably,neuromodulation has garnered considerable attention for its potential to enhance nerve regeneration,provide neuroprotection,restore neurons,and regulate the neural reorganization of circuits within the cerebral cortex and corticospinal tract.To improve the effectiveness of these interventions,the implementation of multitarget early interventional neuromodulation strategies,such as electrical and magnetic stimulation,is recommended to enhance functional recovery across different phases of nerve injury.This review concisely outlines the challenges encountered following spinal cord injury,synthesizes existing neurostimulation techniques while emphasizing neuroprotection,repair,and regeneration of impaired connections,and advocates for multi-targeted,task-oriented,and timely interventions.
基金funded by the Science and Technology Foundation of Chongqing EducationCommission(GrantNo.KJQN202301153)the ScientificResearch Foundation of Chongqing University of Technology(Grant No.2021ZDZ025)the Postgraduate Innovation Foundation of Chongqing University of Technology(Grant No.gzlcx20243524).
文摘In task-oriented dialogue systems, intent, emotion, and actions are crucial elements of user activity. Analyzing the relationships among these elements to control and manage task-oriented dialogue systems is a challenging task. However, previous work has primarily focused on the independent recognition of user intent and emotion, making it difficult to simultaneously track both aspects in the dialogue tracking module and to effectively utilize user emotions in subsequent dialogue strategies. We propose a Multi-Head Encoder Shared Model (MESM) that dynamically integrates features from emotion and intent encoders through a feature fusioner. Addressing the scarcity of datasets containing both emotion and intent labels, we designed a multi-dataset learning approach enabling the model to generate dialogue summaries encompassing both user intent and emotion. Experiments conducted on the MultiWoZ and MELD datasets demonstrate that our model effectively captures user intent and emotion, achieving extremely competitive results in dialogue state tracking tasks.
文摘Objective: The aim of this article is to reflect on the role of theater nurses in a multidisciplinary team, understand the factors that have influenced theater nurses' practice, and improve the authors' clinical practice ultimately.Methods: The author used Smyth's model to guide the process of reflection on the practice issue. Critical reflection, critical emancipatory theory, reflexivity, and critical social theory were used to help the author analyze the factors that have affected theater nurses' practice in the organization.Results: There are gaps between the espoused and enacted theories. A theater nurse's practice is determined by multiple factors, such as political, structural, social, historical, cultural issues, and so on. The hierarchy of the health context could hinder possible changes in theater nurses' practice. To better understand our practice and implement transformation, we should shape a supportive environment,bear in mind the practice motto of "patient-centered" care, and improve our knowledge and reflection skills.Conclusions: Reflection plays a significant role in the advancing of practice among theater nurses and needs to be combined with clinical practice. To provide the best service of care to perioperative patients, a theater nurse should have an insightful understanding of the factors that have influenced her/his behaviors historically, socially, and culturally. By improving their critical reflection skills,practitioners could gain knowledge from experience.
文摘The broad objective of this study was to establish the moderating effect of corporate culture on the relationship between intellectual capital and organizational performance of firms listed on Nairobi Securities Exchange. The review of literature provided conceptual and empirical gaps that formed the basis of the conceptual hypotheses. Two hypotheses were deduced from general objective： Intellectual capital has a significant influence on corporate performance; corporate culture moderates the relationship between intellectual capital and corporate performance. A cross-section research design was adopted. A survey questionnaire was the main tool of data collection and was distributed to the 50 heads of human resource departments in the different firms＇ period covering four financial years from 2009 to 2012. The study also utilized secondary data obtained from Capital Market Authority Statistical bulletins and Nairobi Securities Exchange Handbook 2012-2013 to collect data on financial performance （ROA, ROE, and Dividend Yield）. Data were tested for reliability results showing that study dimensions were reliable, apart from task-oriented culture that had a Cronbach alpha of 0.262, thus being not considered for further analysis; thus the study relied on employee-oriented culture as a measure of corporate culture. The hypotheses were tested using multiple regression analysis and hierarchical regression respectively. Multiple regression analysis showed that intellectual capital had a significant influence on non-financial performance and no significant influence on financial measures of performance （ROA, ROE, and Dividend Yield）. Test for moderation showed that the interaction term was not significant and thus, employee-oriented culture did not moderate the relationship between intellectual capital and corporate performance. The study demonstrates importance of the influence of intellectual capital on non-financial performance of firms listed on Nairobi Securities Exchange. The results show that interplay among human capital, social capital, and organization capital is important for firms listed on Nairobi Securities Exchange and that the firms should nurture the employees into sharing their knowledge by creating internal and external networks and also creating support system within the organization to retain the knowledge.
基金This work was supported in part by the National Natural Science Foundation of China(92067202,92267301 and 62071058).
文摘With the advent of the Internet of Everything(IoE),the concept of fully interconnected systems has become a reality,and the need for seamless communication and interoperability among different industrial systems has become more pressing than ever before.To address the challenges posed by massive data traffic,we demonstrate the potentials of semantic information processing in industrial manufacturing processes and then propose a brief framework of semantic processing and communication system for industrial network.In particular,the scheme is featured with task-orientation and collaborative processing.To illustrate its applicability,we provide examples of time series and images,as typical industrial data sources,for practical tasks,such as lifecycle estimation and surface defect detection.Simulation results show that semantic information processing achieves a more efficient way of information processing and exchanging,compared to conventional methods,which is crucial for handling the demands of future interconnected industrial networks.
文摘Risk communication is a significant challenge in risk management.It serves different purposes;an important one is to improve the public risk awareness and mitigation.Because of the strong spatio-temporal component of natural hazards,maps can play a decisive role in communicating risk information.The application and design of maps for risk communication especially to the public has not been investigated comprehensively.Specific constraints and challenges of risk communication have not been considered systematically in the map design process so far.This study aims at developing a frame for the application and design of interactive risk and hazard maps for the public which is based on the specific constraints and challenges of risk communication.In a literature review it introduces concepts and methods from social sciences and psychology,which have been assessed as important for communicating risk information.The concepts and methods are adapted to map-mediated risk communication according to the approaches of Activity Theory.Communication objectives and tasks which are essential to improve risk mitigation are identified and geovisualization methods for information presentation are related according to the degree which they are able to serve them.Based on this,some principles for map-based risk communication are established.
文摘The human-computer dialogue has recently attracted extensive attention from both academia and industry as an important branch in the field of artificial intelligence(AI).However,there are few studies on the evaluation of large-scale Chinese human-computer dialogue systems.In this paper,we introduce the Second Evaluation of Chinese Human-Computer Dialogue Technology,which focuses on the identification of a user’s intents and intelligent processing of intent words.The Evaluation consists of user intent classification(Task 1)and online testing of task-oriented dialogues(Task 2),the data sets of which are provided by iFLYTEK Corporation.The evaluation tasks and data sets are introduced in detail,and meanwhile,the evaluation results and the existing problems in the evaluation are discussed.
