Optimization Control of Multi-Mode Coupling All-Wheel Drive System for Hybrid Vehicle

The all-wheel drive(AWD)hybrid system is a research focus on high-performance new energy vehicles that can meet the demands of dynamic performance and passing ability.Simultaneous optimization of the power and economy of hybrid vehicles becomes an issue.A unique multi-mode coupling(MMC)AWD hybrid system is presented to realize the distributed and centralized driving of the front and rear axles to achieve vectored distribution and full utilization of the system power between the axles of vehicles.Based on the parameters of the benchmarking model of a hybrid vehicle,the best model-predictive control-based energy management strategy is proposed.First,the drive system model was built after the analysis of the MMC-AWD’s drive modes.Next,three fundamental strategies were established to address power distribution adjustment and battery SOC maintenance when the SOC changed,which was followed by the design of a road driving force observer.Then,the energy consumption rate in the average time domain was processed before designing the minimum fuel consumption controller based on the equivalent fuel consumption coefficient.Finally,the advantage of the MMC-AWD was confirmed by comparison with the dynamic performance and economy of the BYD Song PLUS DMI-AWD.The findings indicate that,in comparison to the comparative hybrid system at road adhesion coefficients of 0.8 and 0.6,the MMC-AWD’s capacity to accelerate increases by 5.26%and 7.92%,respectively.When the road adhesion coefficient is 0.8,0.6,and 0.4,the maximum climbing ability increases by 14.22%,12.88%,and 4.55%,respectively.As a result,the dynamic performance is greatly enhanced,and the fuel savings rate per 100 km of mileage reaches 12.06%,which is also very economical.The proposed control strategies for the new hybrid AWD vehicle can optimize the power and economy simultaneously.

Evaluation of Compatibilizers for Improving Compatibility between Waste Vegetable Oil and Aged Asphalt

Modifying agents 2,2-Bis(4-glycidyloxyphenyl)propane(2BPE)and dibutyl phthalate(DBP)were selected to enhance the compatibility.By using molecular simulation software(Materials Studio,MS),nine systems were constructed,including molecular models of aged asphalt and WVO monomers with 2BPE and/or DBP.The solubility parameters,Flory-Huggins parameters,and interaction energies of these systems were calculated to determine the impact of 2BPE and DBP on the compatibility of WVO and aged asphalt.Results showed that the addition of 2BPE and DBP reduced the difference in the solubility parameters between WVO and aged asphalt,thus improving the compatibility between WVO and aged asphalt.Additionally,using a combination of 2BPE and DBP in both aged asphalt and rejuvenator was found to be more effective than using either 2BPE or DBP alone.Finally,it was determined that evaluating the compatibility of WVO and aged asphalt using Van der Waals potential and non-bonding energy as evaluation indicators was more accurate than using electrostatic potential energy.

Fake News Detection Based on Text-Modal Dominance and Fusing Multiple Multi-Model Clues

In recent years,how to efficiently and accurately identify multi-model fake news has become more challenging.First,multi-model data provides more evidence but not all are equally important.Secondly,social structure information has proven to be effective in fake news detection and how to combine it while reducing the noise information is critical.Unfortunately,existing approaches fail to handle these problems.This paper proposes a multi-model fake news detection framework based on Tex-modal Dominance and fusing Multiple Multi-model Cues(TD-MMC),which utilizes three valuable multi-model clues:text-model importance,text-image complementary,and text-image inconsistency.TD-MMC is dominated by textural content and assisted by image information while using social network information to enhance text representation.To reduce the irrelevant social structure’s information interference,we use a unidirectional cross-modal attention mechanism to selectively learn the social structure’s features.A cross-modal attention mechanism is adopted to obtain text-image cross-modal features while retaining textual features to reduce the loss of important information.In addition,TD-MMC employs a new multi-model loss to improve the model’s generalization ability.Extensive experiments have been conducted on two public real-world English and Chinese datasets,and the results show that our proposed model outperforms the state-of-the-art methods on classification evaluation metrics.

Hypoglycemic Effect of Radix Et Rhizoma Salviae Miltiorrhizae,Guixi Green Tea and Their Compatibility on Mice

[Objectives]To explore the hypoglycemic effect of Radix Et Rhizoma Salviae Miltiorrhizae,Guixi green tea and their compatibility on mice,so as to provide more options for the adjuvant treatment of diabetes and improve the comprehensive utilization value of Guixi green tea.[Methods]After being fed adaptively for 7 d,60 SPF-grade male mice were intraperitoneally injected with alloxouracil(180 mg/kg)to induce hyperglycemia model,from which 35 mice with a successful model were selected.They were randomly divided into 5 groups(Danshen group,green tea group,compatible group,positive control group and blank control group),with 7 animals in each group.The mice in all groups were administered according to the dose of 200 mg/kg once a day for 15 d.After the last administration,their body weight was measured on the 15 th day after fasting for 12 h,and their fasting blood glucose was measured by tail clipping.[Results]After modeling,the mice in each group showed typical hyperglycemia symptoms,namely obvious polydipsia,polyphagia,polyuria and weight loss.Compared with the blank control group,Danshen group and green tea group had obvious hypoglycemic effect(P<0.05),and compatible group had significant hypoglycemic effect(P<0.01).Compared with the blank control group,the weight loss of diabetic mice could also be inhibited in green tea group and compatible group(P<0.05).[Conclusions]Danshen,Guixi green tea and their compatibility had the effect of lowering blood sugar,among which the compatible group had the most obvious effect.

Effects of Radix Puerariae, Radix Rehmanniae and Their Compatibility on Blood Glucose and Blood Lipids in Mice

[Objectives]To explore the effects of the compatibility of Radix Puerariae and Radix Rehmanniae on blood glucose and blood lipids in diabetic mouses.[Methods]Diabetic mouse model was established.The body weight and fasting blood glucose of mice were measured after 7 and 14 d of administration,and the biochemical indicators of blood lipids(TC,HDL-C,and LDL-C)were detected after 14 d of administration.[Results]Compared with the Radix Puerariae group and Radix Rehmanniae group,the compatibility group(1:2)had the best hypoglycemic effect(P<0.05),and TC and LDL-C in the compatibility group(2:1)significantly decreased(P<0.05),while HDL-C in the compatibility group(1:1)significantly increased(P<0.05).[Conclusions]Radix Puerariae,Radix Rehmanniae and their combination can reduce the blood glucose of diabetic mice.The compatibility group(1:2)had a significant hypoglycemic effect(P<0.05),and LDL-C in the compatibility group(2:1)significantly declined,while HDL-C in the compatibility group(1:1)rose significantly.

Rapid evolution of T2/S-RNase genes in Fragaria linked to multiple transitions from self-incompatibility to self-compatibility

The T2/RNase gene family is widespread in eukaryotes,and particular members of this family play critical roles in the gametophytic self-incompatibility(GSI) system in plants.Wild diploid strawberry(Fragaria)species have diversified their sexual systems via self-incompatible and self-compatible traits,yet how these traits evolved in Fragaria remains elusive.By integrating the published and de novo assembled genomes and the newly generated RNA-seq data,members of the RNase T2 gene family were systematically identified in six Fragaria species,including three self-incompatible species(Fragaria nipponica,Fragaria nubicola,and Fragaria viridis) and three self-compatible species(Fragaria nilgerrensis,Fragaria vesca,and Fragaria iinumae).In total,115 RNase T2 genes were identified in the six Fragaria genomes and can be classified into three classes(Ⅰ-Ⅲ) according to phylogenetic analysis.The identified RNase T2 genes could be divided into 22 homologous gene sets according to amino acid sequence similarity and phylogenetic and syntenic relationships.We found that extensive gene loss and pseudogenization coupled with small-scale duplications mainly accounted for variations in the RNase T2 gene numbers in Fragaria.Multiple copies of homologous genes were mainly generated from tandem and segmental duplication events.Furthermore,we newly identified five S-RNase genes in three self-incompatible Fragaria genomes,including two in F.nipponica,two in F.viridis,and one in F.nubicola,which fit for typical features of a pistil determinant,including highly pistil-specific expression,highly polymorphic proteins and alkaline isoelectric point(pI),while no S-RNase genes were found in all three selfcompatible Fragaria species.Surprisingly,these T2/S-RNase genes contain at least one large intron(>10 kb).This study revealed that the rapid evolution of T2/S-RNase genes within the Fragaria genus could be associated with its sexual mode,and repeated evolution of the self-compatible traits in Fragaria was convergent via losses of S-RNase.

Epidemiological Investigation of Brucellosis Spondylitis and Optimal Selection of Clinical Drug Compatibility, Treatment Course and Treatment Plan

Background: Brucellosis is a zoonotic endemic disease, the main source of infection is infected cattle, sheep, pigs and their products. In recent years, the global incidence of brucellosis spondylitis has increased year by year, and it has spread from pastoral areas to semi-agricultural and semi-pastoral areas, agricultural areas and cities. It has changed from a mainly occupational disease to a mainly food-borne disease, and it is also a zoonotic specific spinal infectious disease that WHO and governments around the world pay great attention to. Due to the low cure rate and high recurrence rate of traditional drug therapy regimen. Therefore, to carry out epidemiological investigation and Related research on clinical drug therapy of brucellosis spondylitis has practical significance for improving diagnosis rate, cure rate and reducing recurrence rate. Objective: To analyze the epidemiological characteristics of Brucellosis spondylitis and explore the choice of drugs and the best drug treatment plan, so as to provide scientific basis for improving the prevention and control of the disease and treatment effect. Methods: Clinical epidemiodogical materials were collected from 113 patients with brucellar spondylitis. All these patients were divided into 5 different groups according to 5 kinds of drugs adopted respectively, and then the patients were given different course of treatment. Results: In the 113 patients, brucellar spondylitis morbility of female patients were higher than that of male ones, and the morbility of Bashang were higher than that of Baxia. These patients were infected mainly through browsing and breeding beasts. Lumbars were the major focus of infection. It was very comnlon that two adjacent lumbars were involved in concurrently. L4 was the most common infection location and its demolishment was most serious. The curative effect of group treated with doxycycline was better than that of group treated without doxycycline. If the course of treatment Was increased, the curative effect Was not increased obviously. Conclusions: There are characteristic features in clinical epidemiology of brucell spondylitis. Doxycycline + Rifampicin + Sulfamethoxazole was used as the preferred antibiotic. Using antibiotics adequately and jointly by two courses of treatment for a long time is the most reasonable way to treat the disease and prevent the disease from recurrence.

Enhancing the compatibility of the amyloid-dye hybrid nanostructure for improved photo-biocatalysis

Artificial photosynthesis is significant for renewable energy generation,sustainable development,and environmental protection.Dye-protein hybrids are promising for developing photosynthesis mimics(e.g.,photo-biocatalysis),but their performances are far lower than the plant photosystems,partially because of the incompatibility between dye and the protein matrix that limits excited state electron transfer of the included dyes.Here,using ThT-insulin amyloid assembly as a model system,we proposed that increasing the dye-protein compatibility could lead to the improved photo-biocatalytic performance.A ThT derivative,ThTPD,was designed with the same electron acceptor but extended π-conjugated donor structure.When integrated into the insulin amyloid,the extended π-conjugated donor structure allowed increased binding affinity and energy with the amyloid matrix,thus better electron transport to the mediator to drive the photocatalytic reaction.Meanwhile,compared with ThT, ThTPD exhibited improved light absorption and longer excited state lifetime.The photo-biocatalytic performance of ThTPD-insulin amyloid was greatly improved as compared with that of ThT in reduced nicotinamide adenine dinucleotide(NADH) regeneration.When integrating with NADH-dependent L-glutamate reductase,the efficiency of the ThTPD-insulin amyloid hybrid was 2.8-fold higher than that of ThT in glutamate generation,showing promising feature in biocatalytic solar-to-chemical conversion.

A Multi-mode Electronic Load Sensing Control Scheme with Power Limitation and Pressure Cut-off for Mobile Machinery

In mobile machinery,hydro-mechanical pumps are increasingly replaced by electronically controlled pumps to improve the automation level,but diversified control functions(e.g.,power limitation and pressure cut-off)are integrated into the electronic controller only from the pump level,leading to the potential instability of the overall system.To solve this problem,a multi-mode electrohydraulic load sensing(MELS)control scheme is proposed especially considering the switching stability from the system level,which includes four working modes of flow control,load sensing,power limitation,and pressure control.Depending on the actual working requirements,the switching rules for the different modes and the switching direction(i.e.,the modes can be switched bilaterally or unilaterally)are defined.The priority of different modes is also defined,from high to low:pressure control,power limitation,load sensing,and flow control.When multiple switching rules are satisfied at the same time,the system switches to the control mode with the highest priority.In addition,the switching stability between flow control and pressure control modes is analyzed,and the controller parameters that guarantee the switching stability are obtained.A comparative study is carried out based on a test rig with a 2-ton hydraulic excavator.The results show that the MELS controller can achieve the control functions of proper flow supplement,power limitation,and pressure cut-off,which has good stability performance when switching between different control modes.This research proposes the MELS control method that realizes the stability of multi-mode switching of the hydraulic system of mobile machinery under different working conditions.

Multi-mode Multi-frequency GNSS-IR Combination System for Sea Level Retrieval

With the development of Global Navigation Satellite Systems(GNSS),geodetic GNSS receivers have been utilized to monitor sea levels using GNSS-Interferometry Reflectometry(GNSS-IR)technology.The multi-mode,multi-frequency signals of GPS,GLONASS,Galileo,and Beidou can be used for GNSS-IR sea level retrieval,but combining these retrievals remains problematic.To address this issue,a GNSS-IR sea level retrieval combination system has been developed,which begins by analyzing error sources in GNSS-IR sea level retrieval and establishing and solving the GNSS-IR retrieval equation.This paper focuses on two key points:time window selection and equation stability.The stability of the retrieval combination equations is determined by the condition number of the coefficient matrix within the time window.The impact of ill-conditioned coefficient matrices on the retrieval results is demonstrated using an extreme case of SNR data with only ascending or descending trajectories.After determining the time window and removing ill-conditioned equations,the multi-mode,multi-frequency GNSS-IR retrieval is performed.Results from three International GNSS Service(IGS)stations show that the combination method produces high-precision,high-resolution,and high-reliability sea level retrieval combination sequences.

Exploring the compatibility theory of traditional Chinese medicine formulae:the disassembled prescriptions study

Traditional Chinese medicine(TCM)has become very popular in the treatment of complex diseases worldwide in recent decades.Despite the promising performance of TCM,how herbs work synergistically in a formula and their therapeutic targets remain ambiguous.This largely limits the correct use and modernization of TCM formulas clinically.The study of disassembled prescriptions is important for investigating the compatibility theory of Chinese medicines.By dissecting the mechanisms of TCM formulae,the compatibility principles of some well-known formulae,such as Realgar-Indigo naturalis,have been elucidated to a certain extent.In this review,several common methods of disassembled prescription studies are summarized,including those of single herb or mineral,sub-prescription,active ingredients or effective parts,large formulae,and systems pharmacology studies,as well as the methods of grouping based on the properties or efficacy of Chinese medicines,in order to provide evidence for formulae study.Moreover,some challenges to be addressed in disassembled prescriptions studies have been identified in this review.

Compatibility Rules of Prescriptions of Tibetan Medicine Polygonatum cirrhifolium Based on Data Mining

[Objectives]To study the prescription compatibility rules of the Tibetan medicine Polygonatum cirrhifolium(Polygonati Rhizoma,Huangjing)based on data mining,so as to provide data support for clinical application and new drug development.[Methods]Prescriptions containing Tibetan medicine Huangjing were collected from Tibetan Medicine Prescriptions Encyclopedia and Tibetan Medicine Classic Literature Collection.The Traditional Chinese Medicine Inheritance Computing System(TCMICS 3.0)and R version 4.1.3 were used to mine and analyze the compatibility rules of prescriptions containing Tibetan medicinal material Huangjing,the rules of medication for high-frequency diseases,and the association rules of various medicinal materials.[Results]A total of 124 prescriptions were collected from the classic literature of Tibetan medicine,and the frequency statistical analysis showed that drugs compatible with Huangjing(≥15)included Tianmendong(Root of Cochinchinese Asparagus)(80),Mirabilis himalaica(Edgew.)Heimerl(Himalayan purple jasmine)(72),Jili(Tribuli Fructus)(70),Tibetan Aoruqin(Vicatia coniifolia)(58),Baidoukou(Round Cardamom Fruit)(47),Hezi(Chebulae Fructus)(45),Shouzhangshen(Rhizome of Conic Gymnadenia)(28),Yuganzi(Phyllanthi Fructus)(26),Pomegranate(25),Maohezi(Terminaliae Belliricae Fructus)(24),Zicaorong(Lacca)(23),Rougui(Cinnamomi Cortex)(15).The main diseases were yellow water disease(20),gynecological diseases(19),kidney cold disease(17),and other Tibetan medicine diseases.Association rule analysis showed that the drug combinations with the highest frequency were Huangjing—Tianmendong,Huangjing—Himalayan purple jasmine,and Huangjing—Jili.[Conclusions]The frequency of combined use of Tibetan medicine Huangjing with dry yellow water,tonifying kidney and diuresis,nourishing health,and treating gynecological diseases is relatively high.

Compatibility Rules of Prescriptions of Tibetan Medicinal Material Mirabilis himalaica(Edgew.)Heimerl Based on Data Mining

[Objectives]To study the prescription compatibility rules of the Tibetan medicinal material Mirabilis himalaica(Edgew.)Heimerl(Himalayan purple jasmine)based on data mining,and to provide reference for clinical application and new drug development.[Methods]The literature data were collected and the prescriptions containing Himalayan purple jasmine were sorted and classified by Microsoft Excel 2019 software.The Traditional Chinese Medicine Inheritance Computing System(TCMICS 3.0)was used to statistically analyze the high-frequency drugs and core drug combinations,the frequency of disease treatment,and the rules of"tastes transforming flavors"of drugs.The FP-tree algorithm was used to analyze the association rules among various Tibetan medicinal materials in the prescriptions,and different supports were set to analyze the compatibility rules of the prescriptions.[Results]There were a total of 129 prescriptions containing Himalayan purple jasmine,297 medicinal materials used in combination with it,and 34 Tibetan medicinal materials with a frequency of≥15.The medicinal flavors were mostly sweet,bitter,and pungent.Among the three flavors,bitterness and sweetness were the majority.At the same time,the medicinal properties were blunt,soft,cool,and warm.A total of 130 kinds of diseases were involved,among which 8 kinds of diseases such as gynecology,kidney cold and yellow water disease had a high frequency.Through association rule analysis,33 commonly used core drug combinations were obtained.The support,confidence,and frequency of the five drug combinations[Jili(Tribuli Fructus),Huangjing(Polygonati Rhizoma),Tianmendong(Root of Cochinchinese Asparagus),and Tibetan Aoruqin(Vicatia coniifolia)]→Himalayan purple jasmine were the basic prescription of Tibetan medicine Wudagen Powder.The drug combinations with higher confidence included Bibo(Piperis Longi Fructus)→Himalayan purple jasmine,Pomegranate(Punica granatum→Himalayan purple jasmine,Baidoukou(Round Cardamom Fruit)→Himalayan purple jasmine,Hezi(Chebulae Fructus)→Himalayan purple jasmine.Jili(Tribuli Fructus)→Himalayan purple jasmine,Huangjing(Polygonati Rhizoma)→Himalayan purple jasmine and Tianmendong(Root of Cochinchinese Asparagus)→Himalayan purple jasmine had highest frequency.[Conclusions]Through the TCMICS,this paper analyzed the compatibility rules of commonly used drugs containing Himalayan purple jasmine and the characteristics of the main diseases.It can be seen that Himalayan purple jasmine is sweet in taste and warm in nature.It assists sovereign drugs in the form of ministerial drugs,which enhances the effect of regulating"long"and nourishing,and plays the role of regulating"long",dispelling cold,and reconciling various drugs,which embodies the compatibility rules of sovereign and ministerial drugs of Tibetan medicines.The main diseases of Himalayan purple jasmine are related to"long"regulation,and it is mostly used in the treatment of gynecological diseases after being combined with other drugs to form a prescription.Most drugs in the prescriptions are sweet,which is the therapeutic principle of regulating"long"and nourishing,and verifies the scientific and rational principle of clinical use of Tibetan medicine.In the prescription,the medicinal properties include both warm and cool,and the medicinal taste is sweet and bitter,which is in line with the compatibility theory of"tastes transforming flavors"in traditional Tibetan medicine prescriptions.

Compatibility mechanism of Chinese medicine formula:state of the art and perspectives

Traditional Chinese medicine(TCM)has been practiced in China and surrounding countries for thousands of years and has gradually attracted the attention of Western countries.After reasonable compatibility,TCMs could play the key role of enhancing efficacy and reducing toxicity,which has significant therapeutic advantages in the treatment of complex diseases in clinical practice.While the TCM compatibility is not the simple addition of drugs.Under the appropriate dosage ratio,multiple TCMs can play a synergistic role to realize the overall regulation of TCM treatment.Therefore,it is of critical essential to study the compatibility of TCM formula to promote TCM modernization,new drug development and clinical application.Recently,under the guidance of TCM theory,many researches on the composition,pharmacodynamic activity and pharmacokinetic properties of TCM formula have emerged by integrating new technologies and new methods,revealing the scientific connotation of the compatibility of TCM formula from different perspectives and levels.This paper introduces the research progress of compatibility rules from different levels of compatibility,compatibility for synergistic enhancement and detoxification,and application of cutting-edge technology,with representative cases,in order to provide ideas and references for further study on TCM compatibility.

Method of Multi-Mode Sensor Data Fusion with an Adaptive Deep Coupling Convolutional Auto-Encoder

To address the difficulties in fusing multi-mode sensor data for complex industrial machinery, an adaptive deep coupling convolutional auto-encoder (ADCCAE) fusion method was proposed. First, the multi-mode features extracted synchronously by the CCAE were stacked and fed to the multi-channel convolution layers for fusion. Then, the fused data was passed to all connection layers for compression and fed to the Softmax module for classification. Finally, the coupling loss function coefficients and the network parameters were optimized through an adaptive approach using the gray wolf optimization (GWO) algorithm. Experimental comparisons showed that the proposed ADCCAE fusion model was superior to existing models for multi-mode data fusion.

A Hand Features Based Fusion Recognition Network with Enhancing Multi-Modal Correlation

Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases.

A Comprehensive Survey on Deep Learning Multi-Modal Fusion:Methods,Technologies and Applications

Multi-modal fusion technology gradually become a fundamental task in many fields,such as autonomous driving,smart healthcare,sentiment analysis,and human-computer interaction.It is rapidly becoming the dominant research due to its powerful perception and judgment capabilities.Under complex scenes,multi-modal fusion technology utilizes the complementary characteristics of multiple data streams to fuse different data types and achieve more accurate predictions.However,achieving outstanding performance is challenging because of equipment performance limitations,missing information,and data noise.This paper comprehensively reviews existing methods based onmulti-modal fusion techniques and completes a detailed and in-depth analysis.According to the data fusion stage,multi-modal fusion has four primary methods:early fusion,deep fusion,late fusion,and hybrid fusion.The paper surveys the three majormulti-modal fusion technologies that can significantly enhance the effect of data fusion and further explore the applications of multi-modal fusion technology in various fields.Finally,it discusses the challenges and explores potential research opportunities.Multi-modal tasks still need intensive study because of data heterogeneity and quality.Preserving complementary information and eliminating redundant information between modalities is critical in multi-modal technology.Invalid data fusion methods may introduce extra noise and lead to worse results.This paper provides a comprehensive and detailed summary in response to these challenges.

Towards trustworthy multi-modal motion prediction:Holistic evaluation and interpretability of outputs

Predicting the motion of other road agents enables autonomous vehicles to perform safe and efficient path planning.This task is very complex,as the behaviour of road agents depends on many factors and the number of possible future trajectories can be consid-erable(multi-modal).Most prior approaches proposed to address multi-modal motion prediction are based on complex machine learning systems that have limited interpret-ability.Moreover,the metrics used in current benchmarks do not evaluate all aspects of the problem,such as the diversity and admissibility of the output.The authors aim to advance towards the design of trustworthy motion prediction systems,based on some of the re-quirements for the design of Trustworthy Artificial Intelligence.The focus is on evaluation criteria,robustness,and interpretability of outputs.First,the evaluation metrics are comprehensively analysed,the main gaps of current benchmarks are identified,and a new holistic evaluation framework is proposed.Then,a method for the assessment of spatial and temporal robustness is introduced by simulating noise in the perception system.To enhance the interpretability of the outputs and generate more balanced results in the proposed evaluation framework,an intent prediction layer that can be attached to multi-modal motion prediction models is proposed.The effectiveness of this approach is assessed through a survey that explores different elements in the visualisation of the multi-modal trajectories and intentions.The proposed approach and findings make a significant contribution to the development of trustworthy motion prediction systems for autono-mous vehicles,advancing the field towards greater safety and reliability.

Multi-modal knowledge graph inference via media convergence and logic rule

Media convergence works by processing information from different modalities and applying them to different domains.It is difficult for the conventional knowledge graph to utilise multi-media features because the introduction of a large amount of information from other modalities reduces the effectiveness of representation learning and makes knowledge graph inference less effective.To address the issue,an inference method based on Media Convergence and Rule-guided Joint Inference model(MCRJI)has been pro-posed.The authors not only converge multi-media features of entities but also introduce logic rules to improve the accuracy and interpretability of link prediction.First,a multi-headed self-attention approach is used to obtain the attention of different media features of entities during semantic synthesis.Second,logic rules of different lengths are mined from knowledge graph to learn new entity representations.Finally,knowledge graph inference is performed based on representing entities that converge multi-media features.Numerous experimental results show that MCRJI outperforms other advanced baselines in using multi-media features and knowledge graph inference,demonstrating that MCRJI provides an excellent approach for knowledge graph inference with converged multi-media features.

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.