Recent Advances on Human-Computer Dialogue

Human-Computer dialogue systems provide a natural language based interface between human and computers. They are widely demanded in network information services, intelligent accompanying robots, and so on. A Human-Computer dialogue system typically consists of three parts, namely Natural Language Understanding （NLU）, Dialogue Management （DM） and Natural Language Generation （NLG）. Each part has several different subtasks. Each subtask has been received lots of attentions, many improvements have been achieved on each subtask, respectively. But systems built in traditional pipeline way, where different subtasks are assembled sequently, suffered from some problems such as error accu- mulation and expanding, domain transferring. Therefore, researches on jointly modeling several subtasks in one part or cross different parts have been prompted greatly in recent years, especially the rapid developments on deep neural networks based joint models. There is even a few work aiming to integrate all subtasks of a dialogue system in a single model, namely end-to-end models. This paper introduces two basic frames of current dialogue systems and gives a brief survey on recent advances on variety subtasks at first, and then focuses on joint models for multiple subtasks of dialogues. We review several different joint models including integration of several subtasks inside NLU or NLG, jointly modeling cross NLG and DM, and jointly modeling through NLU, DM and NLG. Both advantages and problems of those joint models are discussed. We consider that the joint models, or end-to-end models, will be one important trend for developing Human-Computer dialogue systems.

Risk identification and safety assessment of human-computer interaction in integrated avionics based on STAMP

To solve the problem of risk identification and quantitative assessment for human-computer interaction(HCI)in complex avionics systems,an HCI safety analysis framework based on system-theoretical process analysis(STPA)and cognitive reliability and error analysis method(CREAM)is proposed.STPACREAM can identify unsafe control actions and find the causal path during the interaction of avionics systems and pilot with the help of formal verification tools automatically.The common performance conditions(CPC)of avionics systems in the aviation environment is established and a quantitative analysis of human failure is carried out.Taking the head-up display(HUD)system interaction process as an example,a case analysis is carried out,the layered safety control structure and formal model of the HUD interaction process are established.For the interactive behavior“Pilots approaching with HUD”,four unsafe control actions and35 causal scenarios are identified and the impact of common performance conditions at different levels on the pilot decision model are analyzed.The results show that HUD's HCI level gradually improves as the scores of CPC increase,and the quality of crew member cooperation and time sufficiency of the task is the key to its HCI.Through case analysis,it is shown that STPACREAM can quantitatively assess the hazards in HCI and identify the key factors that impact safety.

Identification and distribution of 13003 landslides in the northwest margin of Qinghai-Tibet Plateau based on human-computer interaction remote sensing interpretation

The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Tibet Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.

An Evaluation of Chinese Human-Computer Dialogue Technology

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.

An Evaluation of Chinese Human-Computer Dialogue Technology

There is a growing interest in developing human-computer dialogue systems which is an important branch in the field of artificial intelligence(AI).However,the evaluation of large-scale Chinese human-computer dialogues is still a challenging task.To attract more attention to dialogue evaluation work,we held the fourth Evaluation of Chinese Human-Computer Dialogue Technology(ECDT).It consists of few-shot learning in spoken language understanding(SLU)(Task 1)and knowledge-driven multi-turn dialogue competition(Task 2),the data sets of which are provided by Harbin Institute of Technology and Tsinghua University.In this paper,we will introduce the evaluation tasks and data sets in detail.Meanwhile,we will also analyze the evaluation results and the existing problems in the evaluation.

Dynamic constraint and objective generation approach for real-time train rescheduling model under human-computer interaction

Real-time train rescheduling plays a vital role in railway transportation as it is crucial for maintaining punctuality and reliability in rail operations.In this paper,we propose a rescheduling model that incorporates constraints and objectives generated through human-computer interaction.This approach ensures that the model is aligned with practical requirements and daily operational tasks while facilitating iterative train rescheduling.The dispatcher’s empirical knowledge is integrated into the train rescheduling process using a human-computer interaction framework.We introduce six interfaces to dynamically construct constraints and objectives that capture human intentions.By summarizing rescheduling rules,we devise a rule-based conflict detection-resolution heuristic algorithm to effectively solve the formulated model.A series of numerical experiments are presented,demonstrating strong performance across the entire system.Furthermore,theflexibility of rescheduling is enhanced through secondary analysis-driven solutions derived from the outcomes of humancomputer interactions in the previous step.This proposed interaction method complements existing literature on rescheduling methods involving human-computer interactions.It serves as a tool to aid dispatchers in identifying more feasible solutions in accordance with their empirical rescheduling strategies.

贝朗Dialog+血液透析机的典型故障维修四例

贝朗Dialog+血液透析机是德国贝朗公司推出的一款新型的血液透析机,操作简单、数据处理能力较强,目前已经广泛应用于临床[1]。同时,仪器本身参数、应用记录、报警记录等均能被记录在硬盘中,便于维修及保障其及安全性[2]。近年来随着贝朗Dialog+血液透析机临床应用的增加,关于其故障维修的报道也较多[3-5],严重影响临床工作的正常开展。该型号血液透析机在硬件结构布局上相对规范,分别对应电脑控制、超滤、透析液配比、进水除气单元分层式结构,易于发现问题及进行检修[3-4]。基于此,现对贝朗Dialog+血液透析机的故障数据及典型故障维修案例进行分析、总结维修经验,旨在供同行参考。

贝朗Dialog血液透析机DFS自检过程常见故障分析

分析贝朗Dialog血液透析机透析液通路(DFS)自检过程常见故障及应对策略。广西医科大学第一附属医院血液透析室从2022年开始,对贝朗Dialog血液透析机进行强化质量管理。本研究对2021年和2022年贝朗Dialog血液透析机DFS自检过程常见故障进行统计分析,比较设备故障发生情况、医护人员满意度与患者满意度。结果显示,2022年贝朗Dialog血液透析机DFS自检过程故障发生率低于2021年(P<0.05);2022年医护人员对设备的满意度高于2021年(P<0.05);2022年患者对设备的满意度高于2021年(P<0.05),各项数据差异有统计学意义。研究发现,通过分析贝朗Dialog血液透析机的常见故障,强化质量管理,有助于降低设备故障发生率,提高医护人员及患者对设备的满意度。

贝朗Dialog+血液透析机故障维修三例

血液透析机是急、慢性肾功能衰竭患者肾脏替代治疗中最重要的体外循环设备,也是血液净化治疗中应用最为广泛的仪器,被称为“人工肾”。其工作原理如下:将配置合格的透析液和患者血液分置于半透膜两侧,利用两者浓度和渗透压不同产生溶质弥散、渗透和超滤,以清除血液中部分代谢废物和多余水分;被净化的血液经血液监护警报系统后返回患者体内,同时透析后的液体作为透析废液由透析液通路系统排出;如此不断循环往复,完成整个透析过程[1]。

OPTIMIZATION DESIGN OF HYDRAULIC MANIFOLD BLOCKS BASED ON HUMAN-COMPUTER COOPERATIVE GENETIC ALGORITHM

Optimization design of hydraulic manifold blocks (HMB) is studied as acomplex solid spatial layout problem. Based on comprehensive research into structure features anddesign rules of HMB, an optimal mathematical model for this problem is presented. Usinghuman-computer cooperative genetic algorithm (GA) and its hybrid optitation strategies, integratedlayout and connection design schemes of HMB can be automatically optimized. An example is given totestify it.

STUDY ON HUMAN-COMPUTER SYSTEM FOR STABLE VIRTUAL DISASSEMBLY

The cooperative work between human being and computer based on virtual reality (VR) is investigated to plan the disassembly sequences more efficiently. A three-layer model of human-computer cooperative virtual disassembly is built, and the corresponding human-computer system for stable virtual disassembly is developed. In this system, an immersive and interactive virtual disassembly environment has been created to provide planners with a more visual working scene. For cooperative disassembly, an intelligent module of stability analysis of disassembly operations is embedded into the human-computer system to assist planners to implement disassembly tasks better. The supporting matrix for stability analysis of disassembly operations is defined and the method of stability analysis is detailed. Based on the approach, the stability of any disassembly operation can be analyzed to instruct the manual virtual disassembly. At last, a disassembly case in the virtual environment is given to prove the validity of above ideas.

A Study of Electromyogram Based on Human-Computer Interface

In this paper, a new control system based on forearm electromyogram （EMG） is proposed for computer peripheral control and artificial prosthesis control. This control system intends to realize the commands of six pre-defined hand poses： up, down, left, right, yes, and no. In order to research the possibility of using a unified amplifier for both electroencephalogram （EEG） and EMG, the surface forearm EMG data is acquired by a 4-channel EEG measurement system. The Bayesian classifier is used to classify the power spectral density （PSD） of the signal. The experiment result verifies that this control system can supply a high command recognition rate （average 48%） even the EMG data is collected with an EEG system just with single electrode measurement.

Design and Implementation of the Image Interactive System Based on Human-Computer Interaction

Based on the traditional Human-Computer Interaction method which is mainly touch input system, the way of capturing the movement of people by using cameras is proposed. This is a convenient technique which can provide users more experience. In the article, a new way of detecting moving things is given on the basis of development of the image processing technique. The system architecture decides that the communication should be used between two different applications. After considered, named pipe is selected from many ways of communication to make sure that video is keeping in step with the movement from the analysis of the people moving. According to a large amount of data and principal knowledge, thinking of the need of actual project, a detailed system design and realization is finished. The system consists of three important modules: detecting of the people's movement, information transition between applications and video showing in step with people's movement. The article introduces the idea of each module and technique.

Reform of Human-Computer Interaction Course based on Mobile Application Interaction Design

With the popularity of new intelligent mobile devices in people’s lives,the development of mobile applications has paid increasing attention to the interactive experience of users.As the content of traditional Human-Computer Interaction(HCI)course and teaching material is out of date,it cannot meet the needs of mobile application interaction design and enterprises for students.Therefore,we need a new generation HCI course based on intelligent mobile devices to study the relationship between users and systems.The HCI course not only teaches students HCI theory and model,but also needs to cultivate students’interaction-oriented design practical ability.This paper proposes a set of HCI teaching material design and teaching methods for improving HCI class quality on mobile application interaction design,so as to make students more suitable for the employment requirements of enterprises.

Relevant Visual Semantic Context-Aware Attention-Based Dialog

The existing dataset for visual dialog comprises multiple rounds of questions and a diverse range of image contents.However,it faces challenges in overcoming visual semantic limitations,particularly in obtaining sufficient context from visual and textual aspects of images.This paper proposes a new visual dialog dataset called Diverse History-Dialog(DS-Dialog)to address the visual semantic limitations faced by the existing dataset.DS-Dialog groups relevant histories based on their respective Microsoft Common Objects in Context(MSCOCO)image categories and consolidates them for each image.Specifically,each MSCOCO image category consists of top relevant histories extracted based on their semantic relationships between the original image caption and historical context.These relevant histories are consolidated for each image,and DS-Dialog enhances the current dataset by adding new context-aware relevant history to provide more visual semantic context for each image.The new dataset is generated through several stages,including image semantic feature extraction,keyphrase extraction,relevant question extraction,and relevant history dialog generation.The DS-Dialog dataset contains about 2.6 million question-answer pairs,where 1.3 million pairs correspond to existing VisDial’s question-answer pairs,and the remaining 1.3 million pairs include a maximum of 5 image features for each VisDial image,with each image comprising 10-round relevant question-answer pairs.Moreover,a novel adaptive relevant history selection is proposed to resolve missing visual semantic information for each image.DS-Dialog is used to benchmark the performance of previous visual dialog models and achieves better performance than previous models.Specifically,the proposed DSDialog model achieves an 8% higher mean reciprocal rank(MRR),11% higher R@1%,6% higher R@5%,5% higher R@10%,and 8% higher normalized discounted cumulative gain(NDCG)compared to LF.DS-Dialog also achieves approximately 1 point improvement on R@k,mean,MRR,and NDCG compared to the original RVA,and 2 points improvement compared to LF andDualVD.These results demonstrates the importance of the relevant semantic historical context in enhancing the visual semantic relationship between textual and visual representations of the images and questions.

CCPIT Holds Dialog with Foreign Business Associations and Foreign-Invested Enterprises

On August 24,Ren Hongbin,Chairman of the China Council for the Promotion of International Trade(CCPIT),presided over the Dialog with Foreign Business Associations and Foreign-invested Enterprises and listened carefully to the business operations,problems and demands,as well as opinions and suggestions of foreign business associations and foreign-invested enterprises.The participants included 11 representatives from foreign business associations,such as the American Chamber of Commerce in the People’s Republic of China(AmCham China),the European Union Chamber of Commerce in China(EUCCC),the British Chamber of Commerce in China(BCCC),and the China-Italy Chamber of Commerce(CICC),and 16 representatives of foreign-invested enterprises,such as Bayer,Boehringer Ingelheim,Nestle,Starbucks,Cargill,Corning,Intel,Qualcomm,Pfizer,Air Liquide,P&G,MUFG,and SK China.Vice Chairman Zhang Shenfeng of the CCPIT also attended the Dialog.

Critical Dialogic Accounting and Accountability Through Integrated Popular Reporting and Digital Technologies: The City of Bari

Over the past two decades,dialogic accounting research has evolved into a distinct field,expanding into what is now recognized as critical dialogic accounting and accountability(CDAA).The integration of critical dialogic accounting and accountability acknowledges the growing need to recognize diverse pathways within accounting practices,emphasizing the representation of marginalized perspectives,engagement with power dynamics,and the analysis of conflicts,particularly in the context of societal and environmental impacts.Based on these assumptions,the Integrated Popular Reporting(IPR)is intended as a useful practical dialogic tool designed to impartially represent the viewpoints of different stakeholders.The focus extends beyond traditional dialogic accounting,integrating a newer critical lens that explores the implications of digital technology in the reporting process.To explore these advancements,the study investigates the implementation of the City of Bari’s 2020 Integrated Popular Reporting.Leveraging tools such as Talkwalker and employing a longitudinal,interventionist approach along with semi-structured interviews,the study assesses the effects of digital technologies on the dialogic accounting process.The analysis shows that the use of digital technologies has facilitated a more participatory reporting structure,evident in increased citizen engagement and reduced bureaucratic hurdles.Notably,it has enhanced the accuracy of defining citizens’informational needs and addressed pertinent themes ranging from mobility,economy,digitization,regeneration,and employment.Moreover,it underscores the need to address the digital divide and ensure inclusivity across diverse demographics.Ultimately,it contributes to the ongoing discourse on the role of technology in shaping the future of dialogic accounting and its broader implications for societal accountability.

Improved Behavioural Engagement of Students through Low-stakes Online Tests and Immediate Dialogic Feedback

The engagement of students is a recognised challenge for teachers.Technology offers some practical student engagement tools,and this paper examines the use of low-stakes online tests and immediate dialogic feedback to improve behavioural engagement.The academic exploration of low-stakes tests and dialogic feedback has been extensive,and they are credible teaching tools.In this study,we explore the learning benefit of their combination.Postgraduate engineering students’self-reported and learning analytics data shows conclusive evidence of improved behavioural engagement.We measured a 500%increase in the Learning Management System(LMS)page views on the days when we ran the low-stakes tests(each worth 2%of the marks for the subject)and engaged in immediate dialogic feedback.To interpret these results,we draw on theories of behavioural engagement,low-stakes tests,and feedback.We conclude that the combination of low-stakes tests and immediate feedback improves student behavioural engagement.

A NEW APPROACH TO THE DESIGN OF A SYSTEM FOR FEATURE EXTRACTION BASED ON HUMAN-COMPUTER COLLABORATIVE TACTIC

We are involved in an embarrassing situation that the limited capability of automated feature extraction in digital photogrammetric systems cannot satisfy the increasing needs for rapid acquisition of semantic information for applications. Facing this challenge, a new tactic, Human-Computer Collaborative (HCC) tactic, and a corresponding new method, Operator-Object Directed (OOD) method, are proposed for the design of a system for feature extraction from large scale aerial images. We hold that in almost all technical complex systems, full automation will be neither technically feasible nor socially acceptable. The system should be designed to optimize through the cooperative operation with two agents in the system: the hurtan and the computer.

管道式对话系统研究进展及其在医疗领域应用

随着人工智能技术的快速发展,任务型对话系统成为人机交互领域的热点研究方向。管道式方法是其一种经典的设计框架,在任务型对话系统的研究和应用中扮演着重要角色。对管道式任务型对话系统的研究进展进行了综述,并重点探讨了其在医疗领域的应用。首先介绍管道式对话系统各模块的基本原理、评价指标以及常用的数据集。然后,梳理了近年来深度学习技术在管道式对话系统研究中取得的重要进展,并进一步归纳了所用模型的优缺点。接着,重点关注了管道式对话系统在医疗领域的应用,并讨论了医疗对话系统的需求和挑战。最后,总结并展望了未来的研究方向和发展趋势。