Status of clinical applications of artificial intelligence in echocardiography

Artificial intelligence(AI)technology has been increasingly used in medical field with its rapid developments.Echocardiography is one of the best imaging methods for clinical diagnosis of heart diseases,and combining with AI could further improve its diagnostic efficiency.Though the applications of AI in echocardiography remained at a relatively early stage,a variety of automated quantitative and analytical techniques were rapidly emerging and initially entered clinical practice.The status of clinical applications of AI in echocardiography were reviewed in this article.

Deep learning models semi-automatic training system for quality control of transthoracic echocardiography

Objective To explore the value of deep learning(DL)models semi-automatic training system for automatic optimization of clinical image quality control of transthoracic echocardiography(TTE).Methods Totally 1250 TTE videos from 402 patients were retrospectively collected,including 490 apical four chamber(A4C),310 parasternal long axis view of left ventricle(PLAX)and 450 parasternal short axis view of great vessel(PSAX GV).The videos were divided into development set(245 A4C,155 PLAX,225 PSAX GV),semi-automated training set(98 A4C,62 PLAX,90 PSAX GV)and test set(147 A4C,93 PLAX,135 PSAX GV)at the ratio of 5∶2∶3.Based on development set and semi-automatic training set,DL model of quality control was semi-automatically iteratively optimized,and a semi-automatic training system was constructed,then the efficacy of DL models for recognizing TTE views and assessing imaging quality of TTE were verified in test set.Results After optimization,the overall accuracy,precision,recall,and F1 score of DL models for recognizing TTE views in test set improved from 97.33%,97.26%,97.26%and 97.26%to 99.73%,99.65%,99.77%and 99.71%,respectively,while the overall accuracy for assessing A4C,PLAX and PSAX GV TTE as standard views in test set improved from 89.12%,83.87%and 90.37%to 93.20%,90.32%and 93.33%,respectively.Conclusion The developed DL models semi-automatic training system could improve the efficiency of clinical imaging quality control of TTE and increase iteration speed.

Artificial intelligence models based on non-contrast chest CT for measuring bone mineral density

Objective To observe the value of artificial intelligence(AI)models based on non-contrast chest CT for measuring bone mineral density(BMD).Methods Totally 380 subjects who underwent both non-contrast chest CT and quantitative CT(QCT)BMD examination were retrospectively enrolled and divided into training set(n=304)and test set(n=76)at a ratio of 8∶2.The mean BMD of L1—L3 vertebrae were measured based on QCT.Spongy bones of T5—T10 vertebrae were segmented as ROI,radiomics(Rad)features were extracted,and machine learning(ML),Rad and deep learning(DL)models were constructed for classification of osteoporosis(OP)and evaluating BMD,respectively.Receiver operating characteristic curves were drawn,and area under the curves(AUC)were calculated to evaluate the efficacy of each model for classification of OP.Bland-Altman analysis and Pearson correlation analysis were performed to explore the consistency and correlation of each model with QCT for measuring BMD.Results Among ML and Rad models,ML Bagging-OP and Rad Bagging-OP had the best performances for classification of OP.In test set,AUC of ML Bagging-OP,Rad Bagging-OP and DL OP for classification of OP was 0.943,0.944 and 0.947,respectively,with no significant difference(all P>0.05).BMD obtained with all the above models had good consistency with those measured with QCT(most of the differences were within the range of Ax-G±1.96 s),which were highly positively correlated(r=0.910—0.974,all P<0.001).Conclusion AI models based on non-contrast chest CT had high efficacy for classification of OP,and good consistency of BMD measurements were found between AI models and QCT.

Self-supervised learning artificial intelligence noise reduction technology based on the nearest adjacent layer in ultra-low dose CT of urinary calculi

Objective To observe the value of self-supervised deep learning artificial intelligence(AI)noise reduction technology based on the nearest adjacent layer applicated in ultra-low dose CT(ULDCT)for urinary calculi.Methods Eighty-eight urinary calculi patients were prospectively enrolled.Low dose CT(LDCT)and ULDCT scanning were performed,and the effective dose(ED)of each scanning protocol were calculated.The patients were then randomly divided into training set(n=75)and test set(n=13),and a self-supervised deep learning AI noise reduction system based on the nearest adjacent layer constructed with ULDCT images in training set was used for reducing noise of ULDCT images in test set.In test set,the quality of ULDCT images before and after AI noise reduction were compared with LDCT images,i.e.Blind/Referenceless Image Spatial Quality Evaluator(BRISQUE)scores,image noise(SD ROI)and signal-to-noise ratio(SNR).Results The tube current,the volume CT dose index and the dose length product of abdominal ULDCT scanning protocol were all lower compared with those of LDCT scanning protocol(all P<0.05),with a decrease of ED for approximately 82.66%.For 13 patients with urinary calculi in test set,BRISQUE score showed that the quality level of ULDCT images before AI noise reduction reached 54.42%level but raised to 95.76%level of LDCT images after AI noise reduction.Both ULDCT images after AI noise reduction and LDCT images had lower SD ROI and higher SNR than ULDCT images before AI noise reduction(all adjusted P<0.05),whereas no significant difference was found between the former two(both adjusted P>0.05).Conclusion Self-supervised learning AI noise reduction technology based on the nearest adjacent layer could effectively reduce noise and improve image quality of urinary calculi ULDCT images,being conducive for clinical application of ULDCT.

Regarding the Regulatory Sandbox Route and Mechanism for Governance of Artificial Intelligence

The main challenge in AI governance today is striking a balance between controlling AI dangers and fostering AI innovation.Regulators in a number of nations have progressively extended the regulatory sandbox,which was first implemented in the banking sector,to AI governance in an effort to reduce the conflict between regulation and innovation.The AI regulatory sandbox is a new and feasible route for AI governance in China that not only helps to manage the risks of technology application but also prevents inhibiting AI innovation.It keeps inventors'trial-and-error tolerance space inside the regulatory purview while offering a controlled setting for the development and testing of novel AI that hasn't yet been put on the market.By providing full-cycle governance of AI with the principles of agility and inclusive prudence,the regulatory sandbox offers an alternative to the conventional top-down hard regulation,expost regulation,and tight regulation.However,the current system also has inherent limitations and practical obstacles that need to be overcome by a more rational and effective approach.To achieve its positive impact on AI governance,the AI regulatory sandbox system should build and improve the access and exit mechanism,the coordination mechanism between the sandbox and personal information protection,and the mechanisms of exemption,disclosure,and communication.

Research on Multi-modal In-Vehicle Intelligent Personal Assistant Design

Intelligent personal assistants play a pivotal role in in-vehicle systems,significantly enhancing life efficiency,driving safety,and decision-making support.In this study,the multi-modal design elements of intelligent personal assistants within the context of visual,auditory,and somatosensory interactions with drivers were discussed.Their impact on the driver’s psychological state through various modes such as visual imagery,voice interaction,and gesture interaction were explored.The study also introduced innovative designs for in-vehicle intelligent personal assistants,incorporating design principles such as driver-centricity,prioritizing passenger safety,and utilizing timely feedback as a criterion.Additionally,the study employed design methods like driver behavior research and driving situation analysis to enhance the emotional connection between drivers and their vehicles,ultimately improving driver satisfaction and trust.

Enabling Technologies for Autonomous Robotic Systems in Manufacturing

Research of autonomous manufacturing systems is motivated both by the new technical possibilities of cyber-physical systems and by the practical needs of the industry.Autonomous operation in semi-structured industrial environments can now be supported by advanced sensor technologies,digital twins,artificial intelligence and novel communication techniques.These enable real-time monitoring of production processes,situation recognition and prediction,automated and adaptive(re)planning,teamwork and performance improvement by learning.This paper summarizes the main requirements towards autonomous industrial robotics and suggests a generic workflow for realizing such systems.Application case studies will be presented from recent practice at HUN-REN SZTAKI in a broad range of domains such as assembly,welding,grinding,picking and placing,and machining.The various solutions have in common that they use a generic digital twin concept as their core.After making general recommendations for realizing autonomous robotic solutions in the industry,open issues for future research will be discussed.

Prediction of mechanical properties of A357 alloy using artificial neural network

The workpieces of A357 alloy were routinely heat treated to the T6 state in order to gain an adequate mechanical property.The mechanical properties of these workpieces depend mainly on solid-solution temperature,solid-solution time,artificial aging temperature and artificial aging time.An artificial neural network（ANN） model with a back-propagation（BP） algorithm was used to predict mechanical properties of A357 alloy,and the effects of heat treatment processes on mechanical behavior of this alloy were studied.The results show that this BP model is able to predict the mechanical properties with a high accuracy.This model was used to reflect the influence of heat treatments on the mechanical properties of A357 alloy.Isograms of ultimate tensile strength and elongation were drawn in the same picture,which are very helpful to understand the relationship among aging parameters,ultimate tensile strength and elongation.

Design and analysis of a bisected wheel-based cable climbing robot

To inspect inner wires of the cylindrical cables on a cable-stayed bridge, a new bisected wheel-based cable climbing robot is designed. The simple structure and the moving mode are described and the static features of the robot are analyzed. A cable with a diameter of 139 mm is selected as an example to calculate the design parameters of the robot. For safety energysaving landing in the case of electrical system failure, an electric damper based on back electromotive force and a gas damper with a slider-crank mechanism are introduced to exhaust the energy generated by gravity when the robot is slipping down along the cables. A simplified mathematical model is analyzed and the landing velocity is simulated. For the present design, the robot can climb up a cable with diameters varying from 65 to 205 mm with payloads below 3.5 kg. Several climbing experiments performed on real cables confirm that the proposed robot meets the demands of inspection.

COOPERATIVE DESIGN UNDER CONCURRENT ENGINEERING ENVIRONMENT

This paper outlines a concurrent engineering environment that supports interaction between members of a geographically dispersed multidisciplinary team who is engaged in engineering design activities. Some ideas of engineering design, especially conceptual design are reviewed. A deeper scientific analysis of intelligent design is discussed. A new problem solving strategy and methodologies to implement cooperative design are proposed. Finally, a conceptual model of a blackboard system for accomplishing conceptual design automation is presented. Its fundamental principles, system organization and key implementation techniques are investigated in detail.

Method of Growth in Finding the Test Cube of Industrial Robots

In order to find the test cube for industrial robots as specified by ISO 9283, a seed cube is grown up in an irregular working space of the robot, provided that the corners of the cube do not exceed the boundary of the working space. All possible cubes are searched, and the cube with the maximum volume is selected. The calculation examples show that the method of growth can be used for a variety of industrial robots. The method of growth can determine the test cube and test points of irregular working space according to ISO 9283, and can avoid blindness and randomness in the selection of test points.

Research and Implementation of Network Intelligent Management Based on CSCW

This paper analyzes progresses and difficulties of subjects on computer network’s management and artificial intelligence, proposes AGIMA, a new model of network intelligent management, which is based on computer supported cooperative work (CSCW) and combining new technologies such as WWW, Java. AGIMA transfers from information distribution centered mode in traditional network management to computing distribution centered mode, providing intelligence capacity for network management by a whole intelligent agent group. The implementation of AGIMA takes much consideration of openess, scalability, proactive adaptability and friendliness of human computer interface. Authors present properties of intelligent agent in details, and conclude that network intelligence should be cooperation between human and computer.

Review of the creativity support system

Based on the achievements of domestic and foreign scholars,the concept of the creativity support system(CSS)is introduced and two basic characteristics of the CSS are concluded:one is based on information technology,the other is assisting users in creatively solving problems.Then,the rationale as well as the correlative knowledge of the creativity support system is analyzed.Finally,according to the software that has been developed,the creativity support system's characteristics of the function is discussed.

A NOTE ON CONDITIONAL IMPLICATION

It is well known that there exists a tight connection between nonmonotonic reasoning and conditional implication. Many researchers have investigated it from various angles. Among th em, C.Boutilier and P.Lamarre have shown that some conditional implication may b e regarded as the homology of different nonmonotonic consequence relations. In t his paper, based on the plausibility space introduced by Friedman and Halpern, w e characterize the condition logic in which conditional implication is nonmonoto nic, and this result characterizes the conditional implication which may be rega rded as the corresponding object in Meta language for nonmonotonic inference rel ations.

An Exploration of Interpersonal Meanings in Advertising Discourse from Functional Grammar Perspective

Interpersonal function is one of the three metafunctions of language. This paper investigates the interpersonal meanings in Chinese cosmetic advertising discourse from mood, modality and appraise the three aspects. Based on an exploratory study of data of six typical Chinese cosmetic advertising discourses, the paper claims that the distribution of mood and modality has close link with the interpersonal meaning in advertising. The Functional Grammar and Appraisal System help to reveal the interpersonal meanings of the discourse concerned.

Improvement and application of neural network models in development of wrought magnesium alloys

Neural network models of mechanical properties prediction for wrought magnesium alloys were improved by using more reasonable parameters, and were used to develop new types of magnesium alloys. The parameters were confirmed by comparing prediction errors and correlation coefficients of models, which have been built with all the parameters used commonly with training of all permutations and combinations. The application was focused on Mg-Zn-Mn and Mg-Zn-Y-Zr alloys. The prediction of mechanical properties of Mg-Zn-Mn alloys and the effects of mole ratios of Y to Zn on the strengths in Mg-Zn-Y-Zr alloys were investigated by using the improved models. The predicted results are good agreement with the experimental values. A high strength extruded Mg-Zn-Zr-Y alloy was also developed by the models. The applications of the models indicate that the improved models can be used to develop new types of wrought magnesium alloys.

BACKGROUND KNOWLEDGE AND SECONDARY KNOWLEDGE BASES IN LEARNINGS YSTEMS

This paper presents the differences and relations between background knowledge and domain theories in learning systems. The roles they play during learning procedures are discussed. It is emphasized that background knowledge plays an important role in enhancing the ability of a learning system. An explanation based learning system with domain theory in primary knowledge base and background knowledge in secondary knowledge base is introduced as an example. It shows how background knowledge can be used to solve some of the problems caused by incomplete domain theory in an explanation based learning system. The system can accomplish knowledge level learning through purely deductive approach. At last the acquisition of background knowledge is briefly discussed.

Intelligent emergency service system based on wireless sensor and actuator networks

An intelligent emergency service（ IES） system is designed for indoor environments based on a wireless sensor and actuator network（ WSAN） composed of a gateway, sensor nodes, and a multi-robot system（ MRS）. If the MRS receives accident alarm information, the group of robots will navigate to the accident sites and provide corresponding emergency services.According to the characteristics of the MRS, a distributed consensus formation protocol is designed, which can assure that the multiple robots arrive at the accident site in a specified formation. The prototype emergency service system was designed and implemented, and some relevant simulations and experiments were carried out. The results showthat the MRS can successfully provide emergency lighting and failure node replacement services when accidents happen. The effectiveness of the algorithm and the feasibility of the system are verified.

Yield Increasing and Quality Improving Effects of Smash-ridging Method("4453" Effects) and Its Potential in Benefiting the Nation and the People

Yuan Longping proposed that smash-ridging technology could be extend-ed widely nationwide. ln the research, smash-ridging technology reconstruct cultiva-tion layers with loose soils in agricultural fields, creating ＂4453＂ effects, as fol ows： ＂Four increases＂ include to increase loosen soil quantity in cultivation layers, soil nutri-ents use, ＂water pool＂ in soils, and ＂oxygen pool＂ in soils. Four reductions are to reduce soil erosion, carbon emission, salt content and heavy metal in soils. Five resistances refer to improve crop resistance capacity in terms of drought, high tem-perature, lower temperature, disease and lodging. Three improvements indicate to enhance photosynthetic efficiency over 10%, yield in 10%-30% and quality over 5%. lt is researched that without additional chemical fertilizer, yield could increase by 10% by labor force, animal, tractor or smash-ridging machine. What’s more, by smash-ridging cultivation, the depth can be 20 times or higher compared with tractor cultivation, with looser soils. lt is estimated that if smash-ridging cultivation is applied once in agricultural lands in China, present soil layers can be twice as deep as present. Specifical y, the thickness of loose soil-layers could be extended from 10-18 cm at present to 25-35 cm, and natural rainfal would increase by 40 bil ion cm3. After vitalization of soil nutrients, chemical fertilizer would decrease by 7 bil ion kg, and the increased c rops would feed more than 300 mil ion population as per yield at 7 50 kg/hm2.

Effects of Sunflower Artificial Aging on Seed Vigor and Physiological Characteristics

[Objective]The aim was to study the effects of sunflower artificial aging on seed vigor and physiological characteristics.[Method] The varieties of seed germination capacity,vigor of germination,germination index,vigor index,peroxidase（POD） activity,superoxide dismutase（SOD） activity and malondialdehyde（MDA） content for four sunflower germplasms such as＇SunM20＇,＇Deep Purple Minle＇,＇Da San Kui Hua 4＇and＇Ji Kui 24＇were studied under high temperature and high humidity conditions（100% RH,45 ℃） for different days（0 d,2 d,4 d,6 d,8 d,10 d）.[Result]The result showed that the germination capacity,vigor of germination,germination index,vigor index,POD activity,SOD activity declined gradually with the increase of seed aging days,whereas MDA content enhanced by degrees;The diggerences of resistance to artifical aging existed among the four accessions,＇SunM20＇was the most resistant one,and exhibited the strongest seed vigor,highest activities of two protective enzyme（POD,SOD） and lowest content of MDA at the uniform condition,moreover,the seed vigor and protective enzyme activities of＇SunM20＇changed slowest among the four materials during the aging process.[Conclusion]The distinct reduction of POD,SOD activities maybe the main reasons for the decrease of sunflower seed vigor at the artificial aging,and the gradual accumulation of a few MDA accelerated seeds aging.