In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this stu...In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this study,the consistency of printed electrodes was measured by using a confocal microscope and the pressure distribution detected by online pressure monitoring system was compared to investigate the relationship.The results demonstrated the relationship between printing pressure and the consistency of printed electrodes.As printing pressure increases,the ink layer at the corresponding position becomes thicker and that higher printing pressure enhances the consistency of the printed electrodes.The experiment confirms the feasibility of the online pressure monitoring system,which aids in predicting and controlling the consistency of printed electrodes,thereby improving their performance.展开更多
The aim of this article is to explore potential directions for the development of artificial intelligence(AI).It points out that,while current AI can handle the statistical properties of complex systems,it has difficu...The aim of this article is to explore potential directions for the development of artificial intelligence(AI).It points out that,while current AI can handle the statistical properties of complex systems,it has difficulty effectively processing and fully representing their spatiotemporal complexity patterns.The article also discusses a potential path of AI development in the engineering domain.Based on the existing understanding of the principles of multilevel com-plexity,this article suggests that consistency among the logical structures of datasets,AI models,model-building software,and hardware will be an important AI development direction and is worthy of careful consideration.展开更多
Passerine mimics often imitate various vocalizations from other bird species and incorporate these sounds into their song repertoires.While a few anecdotes reported that wild songbirds imitated human-associated sounds...Passerine mimics often imitate various vocalizations from other bird species and incorporate these sounds into their song repertoires.While a few anecdotes reported that wild songbirds imitated human-associated sounds,besides captive parrots and songbirds,systemic and quantitative studies on human-made sound mimicry in wild birds remain scarce.In this study,we investigated the mimetic accuracy and consistency of electric moped sounds imitated by an urban bird,the Chinese Blackbird(Turdus mandarinus).We found that:(1)Only one type of electric moped sound was imitated,i.e.,13 of 26 males mimicked the first part of the antitheft alarm,a phrase containing a series of identical notes.(2)The mimicry produced by male Chinese Blackbirds had fewer notes and lower consistency within phrases compared to the model alarms.(3)The mimicry of male Chinese Blackbirds was imperfect,i.e.,most of the acoustic parameters differed from the model alarms.Additionally,mimetic notes were lower in frequency than the models.Mimetic notes from two areas were also different in acoustic structures,suggesting Chinese Blackbirds might learn mimicry mainly from conspecific neighbors within each area respectively rather than electric mopeds,namely the secondary mimicry.Imperfect mimicry of human-made sounds could result from cost and physical constraints,associated with high consistency,frequency,and repetitions.Consequently,Chinese Blackbirds copied a simplified version of electric moped alarms.We recommend further attention to mimic species inhabiting urban ecosystems to better understand vocal mimicry's adaptation to ongoing urbanization.展开更多
Facial expression datasets commonly exhibit imbalances between various categories or between difficult and simple samples.This imbalance introduces bias into feature extraction within facial expression recognition(FER...Facial expression datasets commonly exhibit imbalances between various categories or between difficult and simple samples.This imbalance introduces bias into feature extraction within facial expression recognition(FER)models,which hinders the algorithm’s comprehension of emotional states and reduces the overall recognition accuracy.A novel FER model is introduced to address these issues.It integrates rebalancing mechanisms to regulate attention consistency and focus,offering enhanced efficacy.Our approach proposes the following improvements:(i)rebalancing weights are used to enhance the consistency between the heatmaps of an original face sample and its horizontally flipped counterpart;(ii)coefficient factors are incorporated into the standard cross entropy loss function,and rebalancing weights are incorporated to fine-tune the loss adjustment.Experimental results indicate that the FER model outperforms the current leading algorithm,MEK,achieving 0.69%and 2.01%increases in overall and average recognition accuracies,respectively,on the RAF-DB dataset.The model exhibits accuracy improvements of 0.49%and 1.01%in the AffectNet dataset and 0.83%and 1.23%in the FERPlus dataset,respectively.These outcomes validate the superiority and stability of the proposed FER model.展开更多
The joint roughness coefficient(JRC) is one of the key parameters for evaluating the shear strength of rock joints.Because of the scale effect in the JRC,reliable JRC values are of great importance for most rock engin...The joint roughness coefficient(JRC) is one of the key parameters for evaluating the shear strength of rock joints.Because of the scale effect in the JRC,reliable JRC values are of great importance for most rock engineering projects.During the collection process of JRC samples,the redundancy or insufficiency of representative rock joint surface topography(RJST) information in serial length JRC samples is the essential reason that affects the reliability of the scale effect results.Therefore,this paper proposes an adaptive sampling method,in which we use the entropy consistency measure Q(a) to evaluate the consistency of the joint morphology information contained in adjacent JRC samples.Then the sampling interval is automatically adjusted according to the threshold Q(at) of the entropy consistency measure to ensure that the degree of change of RJST information between JRC samples is the same,and ultimately makes the representative RJST information in the collected JRC samples more balanced.The application results of actual cases show that the proposed method can obtain the scale effect in the JRC efficiently and reliably.展开更多
Concentrating Solar Power(CSP)is one of the most promising solar technologies for sustainable power generation in countrieswith high solar potential,likeChad.Identifying suitable sites is of great importance for deplo...Concentrating Solar Power(CSP)is one of the most promising solar technologies for sustainable power generation in countrieswith high solar potential,likeChad.Identifying suitable sites is of great importance for deploying solar power plants.This work focuses on the identification of potential sites for the installation of solar power plants in Chad as well as a comparative analysis using the Analytical Hierarchy Process(AHP),Fuzzy Analytical Hierarchy Process(FAHP),and Full Consistency Method(FUCOM).The results show that 35%of the Chadian territory,i.e.,an area of 449,400 km2,is compatible with the implementation of Concentrating Solar Power.The North,North,East,Southeast,and East zones are the most suitable.The main criteria for influence are direct normal irradiation,the soil slope,and the water resource.FUCOM gave a weight of 41.9%for Direct Normal Irradiation(DNI)compared to 32.71%and 31.81%for AHP and FAHP.This method can be applied to other renewable energy technologies such as photovoltaics,wind power,and biomass.Combining its different analyses will be a valuable tool for planning any renewable energy project in Chad.This work should also facilitate the techno-economic analysis of future CSP plants in Chad.展开更多
Hydrogen fuel cell ships are one of the key solutions to achieving zero carbon emissions in shipping.Multi-fuel cell stacks(MFCS)systems are frequently employed to fulfill the power requirements of high-load power equ...Hydrogen fuel cell ships are one of the key solutions to achieving zero carbon emissions in shipping.Multi-fuel cell stacks(MFCS)systems are frequently employed to fulfill the power requirements of high-load power equipment on ships.Compared to single-stack system,MFCS may be difficult to apply traditional energy management strategies(EMS)due to their complex structure.In this paper,a two-layer power allocation strategy for MFCS of a hydrogen fuel cell ship is proposed to reduce the complexity of the allocation task by splitting it into each layer of the EMS.The first layer of the EMSis centered on the Nonlinear Model Predictive Control(NMPC).The Northern Goshawk Optimization(NGO)algorithm is used to solve the nonlinear optimization problem in NMPC,and the local fine search is performed using sequential quadratic programming(SQP).Based on the power allocation results of the first layer,the second layer is centered on a fuzzy rule-based adaptive power allocation strategy(AP-Fuzzy).The membership function bounds of the fuzzy controller are related to the aging level of the MFCS.The Particle Swarm Optimization(PSO)algorithm is used to optimize the parameters of the residual membership function to improve the performance of the proposed strategy.The effectiveness of the proposed EMS is verified by comparing it with the traditional EMS.The experimental results show that the EMS proposed in this paper can ensure reasonable hydrogen consumption,slow down the FC aging and equalize its performance,effectively extend the system life,and ensure that the ship has good endurance after completing the mission.展开更多
The 5E model includes Engagement,Exploration,Explanation,Elaboration,and Evaluation,with“Evaluation”at the end,conflicting with teaching learning-evaluation consistency.Thus,formative levaluation is integrated into ...The 5E model includes Engagement,Exploration,Explanation,Elaboration,and Evaluation,with“Evaluation”at the end,conflicting with teaching learning-evaluation consistency.Thus,formative levaluation is integrated into the first four stages,and a summative evaluation table is designed for the fifth,enabling students to self-evaluate and reflect.Elementary school English picture book teaching is used as an example to demonstrate the optimized model's application.展开更多
With the popularity of the digital human body,monocular three-dimensional(3D)face reconstruction is widely used in fields such as animation and face recognition.Although current methods trained using single-view image...With the popularity of the digital human body,monocular three-dimensional(3D)face reconstruction is widely used in fields such as animation and face recognition.Although current methods trained using single-view image sets perform well in monocular 3D face reconstruction tasks,they tend to rely on the constraints of the a priori model or the appearance conditions of the input images,fundamentally because of the inability to propose an effective method to reduce the effects of two-dimensional(2D)ambiguity.To solve this problem,we developed an unsupervised training framework for monocular face 3D reconstruction using rotational cycle consistency.Specifically,to learn more accurate facial information,we first used an autoencoder to factor the input images and applied these factors to generate normalized frontal views.We then proceeded through a differentiable renderer to use rotational consistency to continuously perceive refinement.Our method provided implicit multi-view consistency constraints on the pose and depth information estimation of the input face,and the performance was accurate and robust in the presence of large variations in expression and pose.In the benchmark tests,our method performed more stably and realistically than other methods that used 3D face reconstruction in monocular 2D images.展开更多
Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been...Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.展开更多
With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to mult...With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to multimodalinformation exchange and fusion, with many methods attempting to integrate unimodal features to generatemultimodal news representations. However, they still need to fully explore the hierarchical and complex semanticcorrelations between different modal contents, severely limiting their performance detecting multimodal falseinformation. This work proposes a two-stage detection framework for multimodal false information detection,called ASMFD, which is based on image aesthetic similarity to segment and explores the consistency andinconsistency features of images and texts. Specifically, we first use the Contrastive Language-Image Pre-training(CLIP) model to learn the relationship between text and images through label awareness and train an imageaesthetic attribute scorer using an aesthetic attribute dataset. Then, we calculate the aesthetic similarity betweenthe image and related images and use this similarity as a threshold to divide the multimodal correlation matrixinto consistency and inconsistencymatrices. Finally, the fusionmodule is designed to identify essential features fordetectingmultimodal false information. In extensive experiments on four datasets, the performance of the ASMFDis superior to state-of-the-art baseline methods.展开更多
Database watermarking technologies provide an effective solution to data security problems by embedding the watermark in the database to prove copyright or trace the source of data leakage.However,when the watermarked...Database watermarking technologies provide an effective solution to data security problems by embedding the watermark in the database to prove copyright or trace the source of data leakage.However,when the watermarked database is used for data mining model building,such as decision trees,it may cause a different mining result in comparison with the result from the original database caused by the distortion of watermark embedding.Traditional watermarking algorithms mainly consider the statistical distortion of data,such as the mean square error,but very few consider the effect of the watermark on database mining.Therefore,in this paper,a consistency preserving database watermarking algorithm is proposed for decision trees.First,label classification statistics and label state transfer methods are proposed to adjust the watermarked data so that the model structure of the watermarked decision tree is the same as that of the original decision tree.Then,the splitting values of the decision tree are adjusted according to the defined constraint equations.Finally,the adjusted database can obtain a decision tree consistent with the original decision tree.The experimental results demonstrated that the proposed algorithm does not corrupt the watermarks,and makes the watermarked decision tree consistent with the original decision tree with a small distortion.展开更多
In this paper,a data consistency condition(DCC)in Radon domain is re-derived from the perspective of Lie transformation group and compared with other two derivations.By carefully observing the proof procedure on the b...In this paper,a data consistency condition(DCC)in Radon domain is re-derived from the perspective of Lie transformation group and compared with other two derivations.By carefully observing the proof procedure on the basis of Lie transformation group,we may have a deeper insight on the essence of this DCC.Moreover,it may help determine whether there are the corresponding counterparts in both image and Radon domains.Following this line of thought,more data consistency conditions will possibly be explored in the future.This is definitely critical as data consistency conditions would be applied to the construction of algorithms for next-generation CT imaging.展开更多
Many migratory birds exhibit interannual consistency in migration schedules,routes and stopover sites.Detecting the interannual consistency in spatiotemporal characteristics helps understand the maintenance of migrati...Many migratory birds exhibit interannual consistency in migration schedules,routes and stopover sites.Detecting the interannual consistency in spatiotemporal characteristics helps understand the maintenance of migration and enables the implementation of targeted conservation measures.We tracked the migration of Whimbrel(Numenius phaeopus)in the East Asian-Australasian Flyway and collected spatiotemporal data from individuals that were tracked for at least two years.Wilcoxon non-parametric tests were used to compare the interannual variations in the dates of departure from and arrival at breeding/nonbreeding sites,and the inter-annual variation in the longitudes when the same individual across the same latitudes.Whimbrels exhibited a high degree of consistency in the use of breeding,nonbreeding,and stopover sites between years.The variation of arrival dates at nonbreeding sites was significantly larger than that of the departure dates from nonbreeding and breeding sites.Repeatedly used stopover sites by the same individuals in multiple years were concentrated in the Yellow Sea coast during northward migration,but were more widespread during southward migration.The stopover duration at repeatedly used sites was significantly longer than that at sites used only once.When flying across the Yellow Sea,Whimbrels breeding in Sakha(Yakutia)exhibited the highest consistency in migration routes in both autumn and spring.Moreover,the consistency in migration routes of Yakutia breeding birds was generally higher than that of birds breeding in Chukotka.Our results suggest that the northward migration schedule of the Whimbrels is mainly controlled by endogenous factors,while the southward migration schedule is less affected by endogenous factors.The repeated use of stopover sites in the Yellow Sea coast suggests this region is important for the migration of Whimbrel,and thus has high conservation value.展开更多
This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance variation.In Experiment 1,we collected fifty mouse devices from the ...This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance variation.In Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and functions.Results show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various brands.The investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late Stage.Results show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real world.The relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style roadmaps.In addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred boundary.The study provides insights into practical problems for designers,manufacturers,and marketers in product design.It not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand consistency.Designers can use these techniques to find features that influence brand style.Then,capture these features as innovative design elements and maintain core brand values.展开更多
Objective To observe the value of grey-level histogram analysis based on T2WI for differentiating consistency of meningioma.Methods Data of 109 patients with meningioma were retrospectively analyzed.The patients were ...Objective To observe the value of grey-level histogram analysis based on T2WI for differentiating consistency of meningioma.Methods Data of 109 patients with meningioma were retrospectively analyzed.The patients were divided into hard group(n=71)and soft group(n=38)according to the consistency of tumors.Tumor ROI was outlined on axial T2WI showing the largest tumor section,gray levels were extracted and histogram analysis was performed.The value of each histogram parameter were compared between groups.Then receiver operating characteristic curve was drawn,and the area under the curve(AUC)was calculated to evaluate the efficiency for differentiating soft and hard meningioma.Results P 1,P 10,P 50,P 90,P 99 and the mean grey levels on T2WI in soft group were all higher than those in hard group(all P<0.05),while the variance,the kurtosis and the skewness were not significantly different between groups(all P>0.05).The differentiating efficiency of P 1,P 10,P 50,P 90,P 99 and the mean grey levels on T2WI were all fine,with AUC of 0.774 to 0.833,and no significant difference was found(all P>0.05).Conclusion Parameters of grey-level histogram analysis such as P 1,P 10,P 50,P 90,P 99 and the mean values based on T2WI were all valuable for differentiating soft and hard meningioma.展开更多
Marketing and design literature suggests that positioning a brand through the gender dimension of brand personality can influence consumers’perceptions of the brand.However,few studies have explored the role of fonts...Marketing and design literature suggests that positioning a brand through the gender dimension of brand personality can influence consumers’perceptions of the brand.However,few studies have explored the role of fonts and brand gender consistency after brand gender-bending.Therefore,this study aims to explore whether the original font can continue to play a role in consumers’gender perceptions of the brand after brand gender-bending,and whether there are differences in perception between consumers of different genders.Based on the gender dimension in brand personality,this study uses logos composed of fonts with different gender traits to conduct a survey among two groups of participants for effective comparison.Six studies were conducted to examine the influence of fonts on brand gender perception during the process of brand gender-bending.The findings first demonstrate that the perception of font traits affects consumers’perception of brand gender traits.After brand gender-bending,the original font is perceived to exhibit opposite-gender or neutral traits,resulting in a decrease in the perception of the original brand’s gender traits.Additionally,there are differences in how consumers of different genders perceive the font and brand traits after gender-bending.展开更多
目的基于文献计量学总结国内外仿制药领域的研究现状及趋势,为进一步研究提供参考。方法通过检索收集中国学术期刊全文数据库(CNKI)、Web of Science数据库中收录的相关文献,借助CiteSpace6.3R2、VOSview1.6.20、文献计量学在线分析平...目的基于文献计量学总结国内外仿制药领域的研究现状及趋势,为进一步研究提供参考。方法通过检索收集中国学术期刊全文数据库(CNKI)、Web of Science数据库中收录的相关文献,借助CiteSpace6.3R2、VOSview1.6.20、文献计量学在线分析平台等探讨本领域的作者机构合作、国家合作概况,并分析关键词共现、聚类、突现等,并对分析结果可视化展示。结果共纳入2564篇文献,其中中文文献641篇,英文文献1923篇。刊文趋势表明,国内外仿制药领域研究的发展趋势基本相同。目前本领域研究已有国际化趋势,但我国的国际合作中心性为0。关键词分析显示,国内外仿制药领域研究内容在保持一致的前提下各有侧重,其研究内容与热点可相互补充借鉴。结论系统分析了2000—2024年间仿制药领域的相关文献,总结了目前全球仿制药领域的研究现状及趋势,并进一步指出国内外研究的异同,可为本领域的进一步研究提供指导。展开更多
图像异常检测旨在识别并定位图像中的异常区域,针对现有算法中不同层次特征信息利用不充分的问题,提出了基于多层次特征融合网络的图像异常检测算法。通过使用融合了异常先验知识的伪异常数据生成算法,对训练集进行了异常数据扩充,将异...图像异常检测旨在识别并定位图像中的异常区域,针对现有算法中不同层次特征信息利用不充分的问题,提出了基于多层次特征融合网络的图像异常检测算法。通过使用融合了异常先验知识的伪异常数据生成算法,对训练集进行了异常数据扩充,将异常检测任务转化为监督学习任务;构建了多层次特征融合网络,将神经网络中不同层次特征进行融合,丰富了特征中的低层纹理信息和高层语义信息,使得用于异常检测的特征更具区分性;训练时,设计了分数约束损失和一致性约束损失,并结合特征约束损失对整个网络模型进行训练。实验结果表明,MVTec数据集上图像级检测接收机工作特性曲线下面积(area under the receiver operating characteristic, AUROC)平均值为98.7%,像素级定位AUROC平均值为97.9%,每区域重叠率平均值为94.2%,均高于现有的异常检测算法。展开更多
文摘In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this study,the consistency of printed electrodes was measured by using a confocal microscope and the pressure distribution detected by online pressure monitoring system was compared to investigate the relationship.The results demonstrated the relationship between printing pressure and the consistency of printed electrodes.As printing pressure increases,the ink layer at the corresponding position becomes thicker and that higher printing pressure enhances the consistency of the printed electrodes.The experiment confirms the feasibility of the online pressure monitoring system,which aids in predicting and controlling the consistency of printed electrodes,thereby improving their performance.
文摘The aim of this article is to explore potential directions for the development of artificial intelligence(AI).It points out that,while current AI can handle the statistical properties of complex systems,it has difficulty effectively processing and fully representing their spatiotemporal complexity patterns.The article also discusses a potential path of AI development in the engineering domain.Based on the existing understanding of the principles of multilevel com-plexity,this article suggests that consistency among the logical structures of datasets,AI models,model-building software,and hardware will be an important AI development direction and is worthy of careful consideration.
基金supported by the National Key Research and Development Program of China(2022YFC3202104)the Western LightKey Laboratory Cooperative Research Cross-Team Project of Chinese Academy of Sciences(xbzg-zdsys-202207)。
文摘Passerine mimics often imitate various vocalizations from other bird species and incorporate these sounds into their song repertoires.While a few anecdotes reported that wild songbirds imitated human-associated sounds,besides captive parrots and songbirds,systemic and quantitative studies on human-made sound mimicry in wild birds remain scarce.In this study,we investigated the mimetic accuracy and consistency of electric moped sounds imitated by an urban bird,the Chinese Blackbird(Turdus mandarinus).We found that:(1)Only one type of electric moped sound was imitated,i.e.,13 of 26 males mimicked the first part of the antitheft alarm,a phrase containing a series of identical notes.(2)The mimicry produced by male Chinese Blackbirds had fewer notes and lower consistency within phrases compared to the model alarms.(3)The mimicry of male Chinese Blackbirds was imperfect,i.e.,most of the acoustic parameters differed from the model alarms.Additionally,mimetic notes were lower in frequency than the models.Mimetic notes from two areas were also different in acoustic structures,suggesting Chinese Blackbirds might learn mimicry mainly from conspecific neighbors within each area respectively rather than electric mopeds,namely the secondary mimicry.Imperfect mimicry of human-made sounds could result from cost and physical constraints,associated with high consistency,frequency,and repetitions.Consequently,Chinese Blackbirds copied a simplified version of electric moped alarms.We recommend further attention to mimic species inhabiting urban ecosystems to better understand vocal mimicry's adaptation to ongoing urbanization.
基金support from the National Natural Science Foundation of China(Grant Number 62477023).
文摘Facial expression datasets commonly exhibit imbalances between various categories or between difficult and simple samples.This imbalance introduces bias into feature extraction within facial expression recognition(FER)models,which hinders the algorithm’s comprehension of emotional states and reduces the overall recognition accuracy.A novel FER model is introduced to address these issues.It integrates rebalancing mechanisms to regulate attention consistency and focus,offering enhanced efficacy.Our approach proposes the following improvements:(i)rebalancing weights are used to enhance the consistency between the heatmaps of an original face sample and its horizontally flipped counterpart;(ii)coefficient factors are incorporated into the standard cross entropy loss function,and rebalancing weights are incorporated to fine-tune the loss adjustment.Experimental results indicate that the FER model outperforms the current leading algorithm,MEK,achieving 0.69%and 2.01%increases in overall and average recognition accuracies,respectively,on the RAF-DB dataset.The model exhibits accuracy improvements of 0.49%and 1.01%in the AffectNet dataset and 0.83%and 1.23%in the FERPlus dataset,respectively.These outcomes validate the superiority and stability of the proposed FER model.
基金supported by the National Natural Science Foundation of China(No.42207175)。
文摘The joint roughness coefficient(JRC) is one of the key parameters for evaluating the shear strength of rock joints.Because of the scale effect in the JRC,reliable JRC values are of great importance for most rock engineering projects.During the collection process of JRC samples,the redundancy or insufficiency of representative rock joint surface topography(RJST) information in serial length JRC samples is the essential reason that affects the reliability of the scale effect results.Therefore,this paper proposes an adaptive sampling method,in which we use the entropy consistency measure Q(a) to evaluate the consistency of the joint morphology information contained in adjacent JRC samples.Then the sampling interval is automatically adjusted according to the threshold Q(at) of the entropy consistency measure to ensure that the degree of change of RJST information between JRC samples is the same,and ultimately makes the representative RJST information in the collected JRC samples more balanced.The application results of actual cases show that the proposed method can obtain the scale effect in the JRC efficiently and reliably.
文摘Concentrating Solar Power(CSP)is one of the most promising solar technologies for sustainable power generation in countrieswith high solar potential,likeChad.Identifying suitable sites is of great importance for deploying solar power plants.This work focuses on the identification of potential sites for the installation of solar power plants in Chad as well as a comparative analysis using the Analytical Hierarchy Process(AHP),Fuzzy Analytical Hierarchy Process(FAHP),and Full Consistency Method(FUCOM).The results show that 35%of the Chadian territory,i.e.,an area of 449,400 km2,is compatible with the implementation of Concentrating Solar Power.The North,North,East,Southeast,and East zones are the most suitable.The main criteria for influence are direct normal irradiation,the soil slope,and the water resource.FUCOM gave a weight of 41.9%for Direct Normal Irradiation(DNI)compared to 32.71%and 31.81%for AHP and FAHP.This method can be applied to other renewable energy technologies such as photovoltaics,wind power,and biomass.Combining its different analyses will be a valuable tool for planning any renewable energy project in Chad.This work should also facilitate the techno-economic analysis of future CSP plants in Chad.
基金supported by the National Key R&D Program of China(2022YFB4301403).
文摘Hydrogen fuel cell ships are one of the key solutions to achieving zero carbon emissions in shipping.Multi-fuel cell stacks(MFCS)systems are frequently employed to fulfill the power requirements of high-load power equipment on ships.Compared to single-stack system,MFCS may be difficult to apply traditional energy management strategies(EMS)due to their complex structure.In this paper,a two-layer power allocation strategy for MFCS of a hydrogen fuel cell ship is proposed to reduce the complexity of the allocation task by splitting it into each layer of the EMS.The first layer of the EMSis centered on the Nonlinear Model Predictive Control(NMPC).The Northern Goshawk Optimization(NGO)algorithm is used to solve the nonlinear optimization problem in NMPC,and the local fine search is performed using sequential quadratic programming(SQP).Based on the power allocation results of the first layer,the second layer is centered on a fuzzy rule-based adaptive power allocation strategy(AP-Fuzzy).The membership function bounds of the fuzzy controller are related to the aging level of the MFCS.The Particle Swarm Optimization(PSO)algorithm is used to optimize the parameters of the residual membership function to improve the performance of the proposed strategy.The effectiveness of the proposed EMS is verified by comparing it with the traditional EMS.The experimental results show that the EMS proposed in this paper can ensure reasonable hydrogen consumption,slow down the FC aging and equalize its performance,effectively extend the system life,and ensure that the ship has good endurance after completing the mission.
基金This paper is funded by Project Information:2023 Guangdong Undergraduate Colleges and Universities Teaching Quality and Teaching Reform Project Construction Project,Project Name:Action Research on Whole-area Nurturing of English Reading Teaching in Universities,Secondary and Primary Schools under the Perspective of Discipline Nurturing.Project serial number:895.
文摘The 5E model includes Engagement,Exploration,Explanation,Elaboration,and Evaluation,with“Evaluation”at the end,conflicting with teaching learning-evaluation consistency.Thus,formative levaluation is integrated into the first four stages,and a summative evaluation table is designed for the fifth,enabling students to self-evaluate and reflect.Elementary school English picture book teaching is used as an example to demonstrate the optimized model's application.
基金Supported by Science and Technology Department Major Innovation Special Fund of Hubei Province of China(2020BAB116)。
文摘With the popularity of the digital human body,monocular three-dimensional(3D)face reconstruction is widely used in fields such as animation and face recognition.Although current methods trained using single-view image sets perform well in monocular 3D face reconstruction tasks,they tend to rely on the constraints of the a priori model or the appearance conditions of the input images,fundamentally because of the inability to propose an effective method to reduce the effects of two-dimensional(2D)ambiguity.To solve this problem,we developed an unsupervised training framework for monocular face 3D reconstruction using rotational cycle consistency.Specifically,to learn more accurate facial information,we first used an autoencoder to factor the input images and applied these factors to generate normalized frontal views.We then proceeded through a differentiable renderer to use rotational consistency to continuously perceive refinement.Our method provided implicit multi-view consistency constraints on the pose and depth information estimation of the input face,and the performance was accurate and robust in the presence of large variations in expression and pose.In the benchmark tests,our method performed more stably and realistically than other methods that used 3D face reconstruction in monocular 2D images.
基金This work was supported by the National Natural Science Foundation of China(72221002,42271375)the Strategic Priority Research Program(XDA28060100)the Informatization Plan Project(CAS-WX2021PY-0109)of the Chinese Academy of Sciences.
文摘Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.
文摘With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to multimodalinformation exchange and fusion, with many methods attempting to integrate unimodal features to generatemultimodal news representations. However, they still need to fully explore the hierarchical and complex semanticcorrelations between different modal contents, severely limiting their performance detecting multimodal falseinformation. This work proposes a two-stage detection framework for multimodal false information detection,called ASMFD, which is based on image aesthetic similarity to segment and explores the consistency andinconsistency features of images and texts. Specifically, we first use the Contrastive Language-Image Pre-training(CLIP) model to learn the relationship between text and images through label awareness and train an imageaesthetic attribute scorer using an aesthetic attribute dataset. Then, we calculate the aesthetic similarity betweenthe image and related images and use this similarity as a threshold to divide the multimodal correlation matrixinto consistency and inconsistencymatrices. Finally, the fusionmodule is designed to identify essential features fordetectingmultimodal false information. In extensive experiments on four datasets, the performance of the ASMFDis superior to state-of-the-art baseline methods.
基金supported by the National Key Research and Development Program of China under Grant 2021YFB2700600the National Natural Science Foundation of China under Grant 62132013 and 61902292+1 种基金the Key Research and Development Programs of Shaanxi under Grants 2021ZDLGY06-03the Truth-Seeking Research Scholarship Fund of Xidian University。
文摘Database watermarking technologies provide an effective solution to data security problems by embedding the watermark in the database to prove copyright or trace the source of data leakage.However,when the watermarked database is used for data mining model building,such as decision trees,it may cause a different mining result in comparison with the result from the original database caused by the distortion of watermark embedding.Traditional watermarking algorithms mainly consider the statistical distortion of data,such as the mean square error,but very few consider the effect of the watermark on database mining.Therefore,in this paper,a consistency preserving database watermarking algorithm is proposed for decision trees.First,label classification statistics and label state transfer methods are proposed to adjust the watermarked data so that the model structure of the watermarked decision tree is the same as that of the original decision tree.Then,the splitting values of the decision tree are adjusted according to the defined constraint equations.Finally,the adjusted database can obtain a decision tree consistent with the original decision tree.The experimental results demonstrated that the proposed algorithm does not corrupt the watermarks,and makes the watermarked decision tree consistent with the original decision tree with a small distortion.
基金supported in partby Shaanxi Provincial Natural Science Foundation of China(No.2023-JC-YB-521)by National Natural Science Foundation of China(NSFC)(No.12475313)+1 种基金Excellent Youth Fund of Shandong Natural Science Foundation(ZR2024YQ066)by Xi'an Science and Technology Program of China(No.23GXFW0065).
文摘In this paper,a data consistency condition(DCC)in Radon domain is re-derived from the perspective of Lie transformation group and compared with other two derivations.By carefully observing the proof procedure on the basis of Lie transformation group,we may have a deeper insight on the essence of this DCC.Moreover,it may help determine whether there are the corresponding counterparts in both image and Radon domains.Following this line of thought,more data consistency conditions will possibly be explored in the future.This is definitely critical as data consistency conditions would be applied to the construction of algorithms for next-generation CT imaging.
基金supported by the National Key Research and Development Program of China(2023YFF1304504)the National Natural Science Foundation of China(31830089 and 31772467)+1 种基金the Science and Technology Department of Shanghai(21DZ1201902)the World Wide Fund for Nature Beijing Office(10003881).
文摘Many migratory birds exhibit interannual consistency in migration schedules,routes and stopover sites.Detecting the interannual consistency in spatiotemporal characteristics helps understand the maintenance of migration and enables the implementation of targeted conservation measures.We tracked the migration of Whimbrel(Numenius phaeopus)in the East Asian-Australasian Flyway and collected spatiotemporal data from individuals that were tracked for at least two years.Wilcoxon non-parametric tests were used to compare the interannual variations in the dates of departure from and arrival at breeding/nonbreeding sites,and the inter-annual variation in the longitudes when the same individual across the same latitudes.Whimbrels exhibited a high degree of consistency in the use of breeding,nonbreeding,and stopover sites between years.The variation of arrival dates at nonbreeding sites was significantly larger than that of the departure dates from nonbreeding and breeding sites.Repeatedly used stopover sites by the same individuals in multiple years were concentrated in the Yellow Sea coast during northward migration,but were more widespread during southward migration.The stopover duration at repeatedly used sites was significantly longer than that at sites used only once.When flying across the Yellow Sea,Whimbrels breeding in Sakha(Yakutia)exhibited the highest consistency in migration routes in both autumn and spring.Moreover,the consistency in migration routes of Yakutia breeding birds was generally higher than that of birds breeding in Chukotka.Our results suggest that the northward migration schedule of the Whimbrels is mainly controlled by endogenous factors,while the southward migration schedule is less affected by endogenous factors.The repeated use of stopover sites in the Yellow Sea coast suggests this region is important for the migration of Whimbrel,and thus has high conservation value.
基金supported in part by a grant,PHA1110214,from MOE,Taiwan.
文摘This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance variation.In Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and functions.Results show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various brands.The investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late Stage.Results show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real world.The relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style roadmaps.In addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred boundary.The study provides insights into practical problems for designers,manufacturers,and marketers in product design.It not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand consistency.Designers can use these techniques to find features that influence brand style.Then,capture these features as innovative design elements and maintain core brand values.
文摘Objective To observe the value of grey-level histogram analysis based on T2WI for differentiating consistency of meningioma.Methods Data of 109 patients with meningioma were retrospectively analyzed.The patients were divided into hard group(n=71)and soft group(n=38)according to the consistency of tumors.Tumor ROI was outlined on axial T2WI showing the largest tumor section,gray levels were extracted and histogram analysis was performed.The value of each histogram parameter were compared between groups.Then receiver operating characteristic curve was drawn,and the area under the curve(AUC)was calculated to evaluate the efficiency for differentiating soft and hard meningioma.Results P 1,P 10,P 50,P 90,P 99 and the mean grey levels on T2WI in soft group were all higher than those in hard group(all P<0.05),while the variance,the kurtosis and the skewness were not significantly different between groups(all P>0.05).The differentiating efficiency of P 1,P 10,P 50,P 90,P 99 and the mean grey levels on T2WI were all fine,with AUC of 0.774 to 0.833,and no significant difference was found(all P>0.05).Conclusion Parameters of grey-level histogram analysis such as P 1,P 10,P 50,P 90,P 99 and the mean values based on T2WI were all valuable for differentiating soft and hard meningioma.
文摘Marketing and design literature suggests that positioning a brand through the gender dimension of brand personality can influence consumers’perceptions of the brand.However,few studies have explored the role of fonts and brand gender consistency after brand gender-bending.Therefore,this study aims to explore whether the original font can continue to play a role in consumers’gender perceptions of the brand after brand gender-bending,and whether there are differences in perception between consumers of different genders.Based on the gender dimension in brand personality,this study uses logos composed of fonts with different gender traits to conduct a survey among two groups of participants for effective comparison.Six studies were conducted to examine the influence of fonts on brand gender perception during the process of brand gender-bending.The findings first demonstrate that the perception of font traits affects consumers’perception of brand gender traits.After brand gender-bending,the original font is perceived to exhibit opposite-gender or neutral traits,resulting in a decrease in the perception of the original brand’s gender traits.Additionally,there are differences in how consumers of different genders perceive the font and brand traits after gender-bending.
文摘目的基于文献计量学总结国内外仿制药领域的研究现状及趋势,为进一步研究提供参考。方法通过检索收集中国学术期刊全文数据库(CNKI)、Web of Science数据库中收录的相关文献,借助CiteSpace6.3R2、VOSview1.6.20、文献计量学在线分析平台等探讨本领域的作者机构合作、国家合作概况,并分析关键词共现、聚类、突现等,并对分析结果可视化展示。结果共纳入2564篇文献,其中中文文献641篇,英文文献1923篇。刊文趋势表明,国内外仿制药领域研究的发展趋势基本相同。目前本领域研究已有国际化趋势,但我国的国际合作中心性为0。关键词分析显示,国内外仿制药领域研究内容在保持一致的前提下各有侧重,其研究内容与热点可相互补充借鉴。结论系统分析了2000—2024年间仿制药领域的相关文献,总结了目前全球仿制药领域的研究现状及趋势,并进一步指出国内外研究的异同,可为本领域的进一步研究提供指导。
文摘图像异常检测旨在识别并定位图像中的异常区域,针对现有算法中不同层次特征信息利用不充分的问题,提出了基于多层次特征融合网络的图像异常检测算法。通过使用融合了异常先验知识的伪异常数据生成算法,对训练集进行了异常数据扩充,将异常检测任务转化为监督学习任务;构建了多层次特征融合网络,将神经网络中不同层次特征进行融合,丰富了特征中的低层纹理信息和高层语义信息,使得用于异常检测的特征更具区分性;训练时,设计了分数约束损失和一致性约束损失,并结合特征约束损失对整个网络模型进行训练。实验结果表明,MVTec数据集上图像级检测接收机工作特性曲线下面积(area under the receiver operating characteristic, AUROC)平均值为98.7%,像素级定位AUROC平均值为97.9%,每区域重叠率平均值为94.2%,均高于现有的异常检测算法。
