The“Opinions on Comprehensively Deepening Curriculum Reform to Fulfill the Fundamental Task of Strengthening Moral Education”,issued by China’s Ministry of Education in 2015,explicitly identified Project-Based Lear...The“Opinions on Comprehensively Deepening Curriculum Reform to Fulfill the Fundamental Task of Strengthening Moral Education”,issued by China’s Ministry of Education in 2015,explicitly identified Project-Based Learning(PBL)as a key strategy for cultivating students’core competencies.Since then,PBL has been widely implemented as a pilot initiative in primary and secondary schools,gaining increasing influence.Analyzing the intellectual foundations of PBL research in China can offer valuable insights into its theoretical and practical dimensions.This study uses CiteSpace to examine 156 PBL-related articles from the CSSCI database,revealing that the knowledge base of PBL research is primarily built on two major domains.The first is the theoretical foundation,characterized by frequently cited literature focusing on the conceptual framework,educational value,interdisciplinary approaches,core competency cultivation,and instructional objectives of PBL.The second is empirical research,where highly cited studies include case analyses across K–12 settings,general high schools,and higher education institutions.Moving forward,future research on PBL should explore its meaning and value from a dual-subject and integrated perspective,expand case studies to include vocational education,and further promote the interdisciplinary development of core competencies through PBL.展开更多
The field of biometric identification has seen significant advancements over the years,with research focusing on enhancing the accuracy and security of these systems.One of the key developments is the integration of d...The field of biometric identification has seen significant advancements over the years,with research focusing on enhancing the accuracy and security of these systems.One of the key developments is the integration of deep learning techniques in biometric systems.However,despite these advancements,certain challenges persist.One of the most significant challenges is scalability over growing complexity.Traditional methods either require maintaining and securing a growing database,introducing serious security challenges,or relying on retraining the entiremodelwhen new data is introduced-a process that can be computationally expensive and complex.This challenge underscores the need for more efficient methods to scale securely.To this end,we introduce a novel approach that addresses these challenges by integrating multimodal biometrics,cancelable biometrics,and incremental learning techniques.This work is among the first attempts to seamlessly incorporate deep cancelable biometrics with dynamic architectural updates,applied incrementally to the deep learning model as new users are enrolled,achieving high performance with minimal catastrophic forgetting.By leveraging a One-Dimensional Convolutional Neural Network(1D-CNN)architecture combined with a hybrid incremental learning approach,our system achieves high recognition accuracy,averaging 98.98% over incrementing datasets,while ensuring user privacy through cancelable templates generated via a pre-trained CNN model and random projection.The approach demonstrates remarkable adaptability,utilizing the least intrusive biometric traits like facial features and fingerprints,ensuring not only robust performance but also long-term serviceability.展开更多
Aiming at the problem of mobile data traffic surge in 5G networks,this paper proposes an effective solution combining massive multiple-input multiple-output techniques with Ultra-Dense Network(UDN)and focuses on solvi...Aiming at the problem of mobile data traffic surge in 5G networks,this paper proposes an effective solution combining massive multiple-input multiple-output techniques with Ultra-Dense Network(UDN)and focuses on solving the resulting challenge of increased energy consumption.A base station control algorithm based on Multi-Agent Proximity Policy Optimization(MAPPO)is designed.In the constructed 5G UDN model,each base station is considered as an agent,and the MAPPO algorithm enables inter-base station collaboration and interference management to optimize the network performance.To reduce the extra power consumption due to frequent sleep mode switching of base stations,a sleep mode switching decision algorithm is proposed.The algorithm reduces unnecessary power consumption by evaluating the network state similarity and intelligently adjusting the agent’s action strategy.Simulation results show that the proposed algorithm reduces the power consumption by 24.61% compared to the no-sleep strategy and further reduces the power consumption by 5.36% compared to the traditional MAPPO algorithm under the premise of guaranteeing the quality of service of users.展开更多
As legal cases grow in complexity and volume worldwide,integrating machine learning and artificial intelligence into judicial systems has become a pivotal research focus.This study introduces a comprehensive framework...As legal cases grow in complexity and volume worldwide,integrating machine learning and artificial intelligence into judicial systems has become a pivotal research focus.This study introduces a comprehensive framework for verdict recommendation that synergizes rule-based methods with deep learning techniques specifically tailored to the legal domain.The proposed framework comprises three core modules:legal feature extraction,semantic similarity assessment,and verdict recommendation.For legal feature extraction,a rule-based approach leverages Black’s Law Dictionary and WordNet Synsets to construct feature vectors from judicial texts.Semantic similarity between cases is evaluated using a hybrid method that combines rule-based logic with an LSTM model,analyzing the feature vectors of query cases against a legal knowledge base.Verdicts are then recommended through a rule-based retrieval system,enhanced by predefined legal statutes and regulations.By merging rule-based methodologies with deep learning,this framework addresses the interpretability challenges often associated with contemporary AImodels,thereby enhancing both transparency and generalizability across diverse legal contexts.The system was rigorously tested using a legal corpus of 43,000 case laws across six categories:Criminal,Revenue,Service,Corporate,Constitutional,and Civil law,ensuring its adaptability across a wide range of judicial scenarios.Performance evaluation showed that the feature extraction module achieved an average accuracy of 91.6%with an F-Score of 95%.The semantic similarity module,tested using Manhattan,Euclidean,and Cosine distance metrics,achieved 88%accuracy and a 93%F-Score for short queries(Manhattan),89%accuracy and a 93.7%F-Score for medium-length queries(Euclidean),and 87%accuracy with a 92.5%F-Score for longer queries(Cosine).The verdict recommendation module outperformed existing methods,achieving 90%accuracy and a 93.75%F-Score.This study highlights the potential of hybrid AI frameworks to improve judicial decision-making and streamline legal processes,offering a robust,interpretable,and adaptable solution for the evolving demands of modern legal systems.展开更多
Fringe projection profilometry(FPP)has been widely applied to non-contact three-dimensional measurement in industries owing to its high accuracy and speed.The point cloud,which is a measurement result of the FPP syste...Fringe projection profilometry(FPP)has been widely applied to non-contact three-dimensional measurement in industries owing to its high accuracy and speed.The point cloud,which is a measurement result of the FPP system,typically contains a large number of invalid points caused by the background,ambient light,shadows,and object edge regions.Research on noisy point detection and elimination has been conducted over the past two decades.However,existing invalid point removal methods are based on image intensity analysis and are only applicable to simple measurement backgrounds that are purely dark.In this paper,we propose a novel invalid point removal framework that consists of two aspects:(1)A convolutional neural network(CNN)is designed to segment the foreground from the background of different intensity conditions in FPP measurement circumstances to remove background points and the most discrete points in background regions.(2)A two-step method based on the fringe image intensity threshold and a bilateral filter is proposed to eliminate the small number of discrete points remaining after background segmentation caused by shadows and edge areas on objects.Experimental results verify that the proposed framework(1)can remove background points intelligently and accurately in different types of complex circumstances,and(2)performs excellently in discrete point detection from object regions.展开更多
Recent advancements in artificial intelligence have transformed three-dimensional(3D)optical imaging and metrology,enabling high-resolution and high-precision 3D surface geometry measurements from one single fringe pa...Recent advancements in artificial intelligence have transformed three-dimensional(3D)optical imaging and metrology,enabling high-resolution and high-precision 3D surface geometry measurements from one single fringe pattern projection.However,the imaging speed of conventional fringe projection profilometry(FPP)remains limited by the native sensor refresh rates due to the inherent"one-to-one"synchronization mechanism between pattern projection and image acquisition in standard structured light techniques.Here,we present dual-frequency angular-multiplexed fringe projection profilometry(DFAMFPP),a deep learning-enabled 3D imaging technique that achieves high-speed,high-precision,and large-depth-range absolute 3D surface measurements at speeds 16 times faster than the sensor's native frame rate.By encoding multi-timeframe 3D information into a single multiplexed image using multiple pairs of dual-frequency fringes,high-accuracy absolute phase maps are reconstructed using specially trained two-stage number-theoretical-based deep neural networks.We validate the effectiveness of DFAMFPP through dynamic scene measurements,achieving 10,000 Hz 3D imaging of a running turbofan engine prototype with only a 625 Hz camera.By overcoming the sensor hardware bottleneck,DFAMFPP significantly advances high-speed and ultra-high-speed 3D imaging,opening new avenues for exploring dynamic processes across diverse scientific disciplines.展开更多
The sampling of the training data is a bottleneck in the development of artificial intelligence(AI)models due to the processing of huge amounts of data or to the difficulty of access to the data in industrial practice...The sampling of the training data is a bottleneck in the development of artificial intelligence(AI)models due to the processing of huge amounts of data or to the difficulty of access to the data in industrial practices.Active learning(AL)approaches are useful in such a context since they maximize the performance of the trained model while minimizing the number of training samples.Such smart sampling methodologies iteratively sample the points that should be labeled and added to the training set based on their informativeness and pertinence.To judge the relevance of a data instance,query rules are defined.In this paper,we propose an AL methodology based on a physics-based query rule.Given some industrial objectives from the physical process where the AI model is implied in,the physics-based AL approach iteratively converges to the data instances fulfilling those objectives while sampling training points.Therefore,the trained surrogate model is accurate where the potentially interesting data instances from the industrial point of view are,while coarse everywhere else where the data instances are of no interest in the industrial context studied.展开更多
This study focuses on the effectiveness of the project-based language learning(PBLL) in a college Secretarial Oral English(SOE) Module. Student reflections of the language project work have been analyzed through Activ...This study focuses on the effectiveness of the project-based language learning(PBLL) in a college Secretarial Oral English(SOE) Module. Student reflections of the language project work have been analyzed through Activity Theory. Moreover,Data has been collected and categorized based on the components of complex human activity: the subject, object, tools(signs,symbols, and language), the community in which the activity take place, division of labor, and rules. The findings theoretically support the outcome of project-based language learning which align with the object of the activity.展开更多
This study aims to explore Chinese university EFL learners'perceptions toward alternative assessment in a context of a project-based learning digital storytelling presentation in Speaking Course.It also seeks to c...This study aims to explore Chinese university EFL learners'perceptions toward alternative assessment in a context of a project-based learning digital storytelling presentation in Speaking Course.It also seeks to compare the relationship between alternative assessment and teacher assessment.The findings showed that a strong correlation between alternative assessment and teacher assessment occurred.Alternative assessment activities are viewed by students as"authentic"assessments,as they mimic how the student will be using their knowledge in the future.Alternative assessment as a form of formative assessment can be a powerful day-to-day tool for teachers and students.Alternative assessment is an enabler of process of learning.The study suggests that alternative assessment can encourage learners to become more fully responsible for their learning and can result in more and better learning.Alternative assessment can thus be used as a golden key to the"deaf and dumb"phenomenon for Chinese university EFL learners.展开更多
In this paper,we report the experience received from the project-based learning activity in a fundamental chemistry course.We involved the first year students in Faculty of Engineering at King Mongkut’s University of...In this paper,we report the experience received from the project-based learning activity in a fundamental chemistry course.We involved the first year students in Faculty of Engineering at King Mongkut’s University of Technology Thonburi,Ratchaburi Learning Center,Thailand.This work considers the innovative activities performed in the field of chemistry and physics.This activity has been intensively implemented in teaching first year students.A project has been created to build up a small machine for measuring the concentration of sucrose solutions.The students participated in a project based learning(PBL)process,in which they worked in groups to create the instrument designed to measure the sucrose concentration in percentage by weight of sucrose in pure water solvent.Project-based learning has gained a greater position in the classroom as researchers have documented what teachers have long understood:Students become more engaged in learning when they have a chance to dig into complex and challenging problems that closely resemble real life.Moreover,several surveys have been conducted along one academic year to evaluate the impact of this method.The results of the surveys show that PBL encourages students’motivation and improves their knowledge involving the project.It is also pointed out that this methodology requires more dedication from lecturers than traditional methodology.展开更多
Universities teach mainly specialized subjects and the liberal arts. Society expects university students to gain certain basic skills important when working for a company. These skills can be divided broadly into acti...Universities teach mainly specialized subjects and the liberal arts. Society expects university students to gain certain basic skills important when working for a company. These skills can be divided broadly into action, thinking, and teamwork. The purpose of this paper is to propose a method of project-based education for developing fundamental competencies for working persons. Many studies have been reported on educational methods with project management techniques, but few have considered project-based education aiming at improving fundamental competencies for working persons. If these competencies can be developed through project-based education, it will be possible to develop not only teamwork skills, but also a wide range of skills involving action as well as thinking. The traditional Japanese university curriculum comprises specialized subjects and the liberal arts. The author proposes the addition of project-based education to develop basic skills needed in the workforce. This research proposes an education model for basic competency training and examines the educational outcomes by studying results of a cooking tool project assigned to university students. The model includes Teoriya Resheniya Izobretatelskikh Zadatch （TRIZ, a Russian acronym for the theory of inventive problem solving）, a World Cafe, and the SECI process （a process of knowledge creation comprised of socialization, externalization, combination, and internalization in knowledge management） in the hope that this model will be conducive to implementing effective project-based learning. This research concludes that it is possible to develop the basic skills needed by university students in society through project-based learning under a basic skills education model.展开更多
In this article, authors describe how to use the project-based learning （PBL） pedagogy to enhance students＇ Calculus learning based on the first author＇s experimental teaching experience. The ＂2014 BMCC Polar Art...In this article, authors describe how to use the project-based learning （PBL） pedagogy to enhance students＇ Calculus learning based on the first author＇s experimental teaching experience. The ＂2014 BMCC Polar Art Calendar＂ project was completed by Calculus students at Borough of Manhattan Community College （BMCC） during the fall 2013 semester. Students were requested to apply graphs of polar equations to create computer-generated images with a variety of flower patterns by using the Maple technology in a math lab. At the end of this project, students were requested to submit and present their written reports to express their mathematical thinking. Authors also explain in details how to create projects compatible with textbook knowledge learning objectives, how to prepare scaffolding materials for students to use, how to utilize a math lab and to work with lab technicians in Maple Software, and how to design a rubric for project evaluations. Students＇ artwork created in the Polar Art Calendar are presented. Students＇ positive outcomes have proven a success of this project design as well as its execution as an example of PBL. Benefits to students and challenges to teachers on the use of PBL approach have been discussed at the end of this article.展开更多
This thesis sketches the connotation of project-based learning and introduces the basis on which project-based learning is practiced and applied in school of software as well as the plan of further practicing project-...This thesis sketches the connotation of project-based learning and introduces the basis on which project-based learning is practiced and applied in school of software as well as the plan of further practicing project-based learning.At the same time,this thesis also discusses application of project-based learning in "education and cultivation plan of excellent engineer".展开更多
All engineering students need to develop their important skills of leadership in project management. Many students have never been leaders in their social and school lives. A leading role is unimaginable to them and h...All engineering students need to develop their important skills of leadership in project management. Many students have never been leaders in their social and school lives. A leading role is unimaginable to them and hence they cannot imagine how to achieve it. The purpose of this paper is to report a result of a new leadership education program which links a variety of simulated experiences with real actions of students in project based learning （PBL） to develop their leadership ability. The first step is for graduate students to gain knowledge in the leadership arena. Then, they utilize simulation to experience leadership actions many times. Simulation provides a safe environment in which they can try out many different approaches in taking leadership in various situations. In the next step, students as a team utilize PBL, so that the above simulated experiences can help them to actually take leadership. Students can apply trained leadership to actual projects. It is highly effective to apply conscious leadership to a project aimed at a specific goal in limited circumstances. This education repeats both of the steps above, raising leadership abilities in an upward spiral. In terms of students＇ evaluation of leadership education in project management, 360-degree assessments were carried out by teachers, senior, and junior students before and after the course, and authors compare their assessments thoroughly. As a result, authors are assured that students not only gained knowledge but also raised leadership abilities in their actions after this education. Six months after the time of leadership education employing simulated experiences and PBL, follow-up interviews were conducted on its effects. Authors recognized the cyclic period that students apply simulated experiences to PBL and that they seek different approaches in simulation for solving problems found in reality. This research concludes that this cycle of simulator and PBL can produce effective leadership actions.展开更多
The Wavelet-Domain Projection Pursuit Learning Network (WDPPLN) is proposedfor restoring degraded image. The new network combines the advantages of both projectionpursuit and wavelet shrinkage. Restoring image is very...The Wavelet-Domain Projection Pursuit Learning Network (WDPPLN) is proposedfor restoring degraded image. The new network combines the advantages of both projectionpursuit and wavelet shrinkage. Restoring image is very difficult when little is known about apriori knowledge for multisource degraded factors. WDPPLN successfully resolves this problemby separately processing wavelet coefficients and scale coefficients. Parameters in WDPPLN,which are used to simulate degraded factors, are estimated via WDPPLN training, using scalecoefficients. Also, WDPPLN uses soft-threshold of wavelet shrinkage technique to suppress noisein three high frequency subbands. The new method is compared with the traditional methodsand the Projection Pursuit Learning Network (PPLN) method. Experimental results demonstratethat it is an effective method for unsupervised restoring degraded image.展开更多
A growing number of studies are now emphasizing the critical importance of learning and knowledge accumulation for firm-level competitiveness. Despite the growing awareness, relatively fewer project-based firms have i...A growing number of studies are now emphasizing the critical importance of learning and knowledge accumulation for firm-level competitiveness. Despite the growing awareness, relatively fewer project-based firms have institutionalized mechanisms to systematically capture new project knowledge and re-use it to improve the execution of subsequent projects. The peculiarity of projects presents unique challenges that make the cognitive approach to learning difficult to implement. As such, researchers are recommending the social constructivist perspective of learning as the most viable strategy for cultivating learning within and across projects. However, scant work has been undertaken from this sociological perspective to analyze how temporary organizations manage knowledge arising from and relating to projects. From this standpoint, the aim of this paper is to discuss the learning mechanisms of construction firms. The study adopted a quantitative strategy by employing a questionnaire survey into the learning practices of construction projects in Ghana. Drawing on preliminary findings from the literature, the study proposes a model for cultivating learning within projects from the social constructivist viewpoint. In the model, project management practitioners can purposefully nurture or structure a project learning activity through four mechanisms <em>viz</em>.: <em>institutionalization, externalization, socialization and internalization</em>. The proposed model is subsequently validated in an empirical study into the learning practices during the implementation of construction projects in Ghana. Based on the empirical results, it seems that knowledge sharing and transfers through the four aforementioned learning mechanisms proposed by the model are highly regarded within project management practice in Ghana.展开更多
基金Provincial-Level Quality Engineering Project,Preschool Education Teacher Training Base of Fuyang Normal University(Project No.:2023cyts023)University-Level Research Team Project,Collaborative Innovation Center for Basic Education in Northern Anhui(Project No.:kytd202418)。
文摘The“Opinions on Comprehensively Deepening Curriculum Reform to Fulfill the Fundamental Task of Strengthening Moral Education”,issued by China’s Ministry of Education in 2015,explicitly identified Project-Based Learning(PBL)as a key strategy for cultivating students’core competencies.Since then,PBL has been widely implemented as a pilot initiative in primary and secondary schools,gaining increasing influence.Analyzing the intellectual foundations of PBL research in China can offer valuable insights into its theoretical and practical dimensions.This study uses CiteSpace to examine 156 PBL-related articles from the CSSCI database,revealing that the knowledge base of PBL research is primarily built on two major domains.The first is the theoretical foundation,characterized by frequently cited literature focusing on the conceptual framework,educational value,interdisciplinary approaches,core competency cultivation,and instructional objectives of PBL.The second is empirical research,where highly cited studies include case analyses across K–12 settings,general high schools,and higher education institutions.Moving forward,future research on PBL should explore its meaning and value from a dual-subject and integrated perspective,expand case studies to include vocational education,and further promote the interdisciplinary development of core competencies through PBL.
基金the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through project number RI-44-0833.
文摘The field of biometric identification has seen significant advancements over the years,with research focusing on enhancing the accuracy and security of these systems.One of the key developments is the integration of deep learning techniques in biometric systems.However,despite these advancements,certain challenges persist.One of the most significant challenges is scalability over growing complexity.Traditional methods either require maintaining and securing a growing database,introducing serious security challenges,or relying on retraining the entiremodelwhen new data is introduced-a process that can be computationally expensive and complex.This challenge underscores the need for more efficient methods to scale securely.To this end,we introduce a novel approach that addresses these challenges by integrating multimodal biometrics,cancelable biometrics,and incremental learning techniques.This work is among the first attempts to seamlessly incorporate deep cancelable biometrics with dynamic architectural updates,applied incrementally to the deep learning model as new users are enrolled,achieving high performance with minimal catastrophic forgetting.By leveraging a One-Dimensional Convolutional Neural Network(1D-CNN)architecture combined with a hybrid incremental learning approach,our system achieves high recognition accuracy,averaging 98.98% over incrementing datasets,while ensuring user privacy through cancelable templates generated via a pre-trained CNN model and random projection.The approach demonstrates remarkable adaptability,utilizing the least intrusive biometric traits like facial features and fingerprints,ensuring not only robust performance but also long-term serviceability.
基金supported by National Natural Science Foundation of China(62271096,U20A20157)Natural Science Foundation of Chongqing,China(CSTB2023NSCQ-LZX0134)+3 种基金University Innovation Research Group of Chongqing(CXQT20017)Youth Innovation Group Support Program of ICE Discipline of CQUPT(SCIE-QN-2022-04)the Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN202300632)the Chongqing Postdoctoral Special Funding Project(2022CQBSHTB2057).
文摘Aiming at the problem of mobile data traffic surge in 5G networks,this paper proposes an effective solution combining massive multiple-input multiple-output techniques with Ultra-Dense Network(UDN)and focuses on solving the resulting challenge of increased energy consumption.A base station control algorithm based on Multi-Agent Proximity Policy Optimization(MAPPO)is designed.In the constructed 5G UDN model,each base station is considered as an agent,and the MAPPO algorithm enables inter-base station collaboration and interference management to optimize the network performance.To reduce the extra power consumption due to frequent sleep mode switching of base stations,a sleep mode switching decision algorithm is proposed.The algorithm reduces unnecessary power consumption by evaluating the network state similarity and intelligently adjusting the agent’s action strategy.Simulation results show that the proposed algorithm reduces the power consumption by 24.61% compared to the no-sleep strategy and further reduces the power consumption by 5.36% compared to the traditional MAPPO algorithm under the premise of guaranteeing the quality of service of users.
基金funded by the Deanship of Scientific Research at Jouf University under Grant number DSR-2022-RG-0101。
文摘As legal cases grow in complexity and volume worldwide,integrating machine learning and artificial intelligence into judicial systems has become a pivotal research focus.This study introduces a comprehensive framework for verdict recommendation that synergizes rule-based methods with deep learning techniques specifically tailored to the legal domain.The proposed framework comprises three core modules:legal feature extraction,semantic similarity assessment,and verdict recommendation.For legal feature extraction,a rule-based approach leverages Black’s Law Dictionary and WordNet Synsets to construct feature vectors from judicial texts.Semantic similarity between cases is evaluated using a hybrid method that combines rule-based logic with an LSTM model,analyzing the feature vectors of query cases against a legal knowledge base.Verdicts are then recommended through a rule-based retrieval system,enhanced by predefined legal statutes and regulations.By merging rule-based methodologies with deep learning,this framework addresses the interpretability challenges often associated with contemporary AImodels,thereby enhancing both transparency and generalizability across diverse legal contexts.The system was rigorously tested using a legal corpus of 43,000 case laws across six categories:Criminal,Revenue,Service,Corporate,Constitutional,and Civil law,ensuring its adaptability across a wide range of judicial scenarios.Performance evaluation showed that the feature extraction module achieved an average accuracy of 91.6%with an F-Score of 95%.The semantic similarity module,tested using Manhattan,Euclidean,and Cosine distance metrics,achieved 88%accuracy and a 93%F-Score for short queries(Manhattan),89%accuracy and a 93.7%F-Score for medium-length queries(Euclidean),and 87%accuracy with a 92.5%F-Score for longer queries(Cosine).The verdict recommendation module outperformed existing methods,achieving 90%accuracy and a 93.75%F-Score.This study highlights the potential of hybrid AI frameworks to improve judicial decision-making and streamline legal processes,offering a robust,interpretable,and adaptable solution for the evolving demands of modern legal systems.
基金Supported by National Defense Basic Scientific Research Program of China(Grant No.JCKY2021602B032)。
文摘Fringe projection profilometry(FPP)has been widely applied to non-contact three-dimensional measurement in industries owing to its high accuracy and speed.The point cloud,which is a measurement result of the FPP system,typically contains a large number of invalid points caused by the background,ambient light,shadows,and object edge regions.Research on noisy point detection and elimination has been conducted over the past two decades.However,existing invalid point removal methods are based on image intensity analysis and are only applicable to simple measurement backgrounds that are purely dark.In this paper,we propose a novel invalid point removal framework that consists of two aspects:(1)A convolutional neural network(CNN)is designed to segment the foreground from the background of different intensity conditions in FPP measurement circumstances to remove background points and the most discrete points in background regions.(2)A two-step method based on the fringe image intensity threshold and a bilateral filter is proposed to eliminate the small number of discrete points remaining after background segmentation caused by shadows and edge areas on objects.Experimental results verify that the proposed framework(1)can remove background points intelligently and accurately in different types of complex circumstances,and(2)performs excellently in discrete point detection from object regions.
基金supported by National Key Research and Development Program of China(2022YFB2804603,2022YFB2804605)National Natural Science Foundation of China(U21B2033)+4 种基金Fundamental Research Funds forthe Central Universities(2023102001,2024202002)National Key Laborato-ry of Shock Wave and Detonation Physics(JCKYS2024212111)China Post-doctoral Science Fund(2023T160318)Open Research Fund of JiangsuKey Laboratory of Spectral Imaging&Intelligent Sense(JSGP202105,JSGP202201)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX25_0695,SJCX25_0188)。
文摘Recent advancements in artificial intelligence have transformed three-dimensional(3D)optical imaging and metrology,enabling high-resolution and high-precision 3D surface geometry measurements from one single fringe pattern projection.However,the imaging speed of conventional fringe projection profilometry(FPP)remains limited by the native sensor refresh rates due to the inherent"one-to-one"synchronization mechanism between pattern projection and image acquisition in standard structured light techniques.Here,we present dual-frequency angular-multiplexed fringe projection profilometry(DFAMFPP),a deep learning-enabled 3D imaging technique that achieves high-speed,high-precision,and large-depth-range absolute 3D surface measurements at speeds 16 times faster than the sensor's native frame rate.By encoding multi-timeframe 3D information into a single multiplexed image using multiple pairs of dual-frequency fringes,high-accuracy absolute phase maps are reconstructed using specially trained two-stage number-theoretical-based deep neural networks.We validate the effectiveness of DFAMFPP through dynamic scene measurements,achieving 10,000 Hz 3D imaging of a running turbofan engine prototype with only a 625 Hz camera.By overcoming the sensor hardware bottleneck,DFAMFPP significantly advances high-speed and ultra-high-speed 3D imaging,opening new avenues for exploring dynamic processes across diverse scientific disciplines.
文摘The sampling of the training data is a bottleneck in the development of artificial intelligence(AI)models due to the processing of huge amounts of data or to the difficulty of access to the data in industrial practices.Active learning(AL)approaches are useful in such a context since they maximize the performance of the trained model while minimizing the number of training samples.Such smart sampling methodologies iteratively sample the points that should be labeled and added to the training set based on their informativeness and pertinence.To judge the relevance of a data instance,query rules are defined.In this paper,we propose an AL methodology based on a physics-based query rule.Given some industrial objectives from the physical process where the AI model is implied in,the physics-based AL approach iteratively converges to the data instances fulfilling those objectives while sampling training points.Therefore,the trained surrogate model is accurate where the potentially interesting data instances from the industrial point of view are,while coarse everywhere else where the data instances are of no interest in the industrial context studied.
文摘This study focuses on the effectiveness of the project-based language learning(PBLL) in a college Secretarial Oral English(SOE) Module. Student reflections of the language project work have been analyzed through Activity Theory. Moreover,Data has been collected and categorized based on the components of complex human activity: the subject, object, tools(signs,symbols, and language), the community in which the activity take place, division of labor, and rules. The findings theoretically support the outcome of project-based language learning which align with the object of the activity.
文摘This study aims to explore Chinese university EFL learners'perceptions toward alternative assessment in a context of a project-based learning digital storytelling presentation in Speaking Course.It also seeks to compare the relationship between alternative assessment and teacher assessment.The findings showed that a strong correlation between alternative assessment and teacher assessment occurred.Alternative assessment activities are viewed by students as"authentic"assessments,as they mimic how the student will be using their knowledge in the future.Alternative assessment as a form of formative assessment can be a powerful day-to-day tool for teachers and students.Alternative assessment is an enabler of process of learning.The study suggests that alternative assessment can encourage learners to become more fully responsible for their learning and can result in more and better learning.Alternative assessment can thus be used as a golden key to the"deaf and dumb"phenomenon for Chinese university EFL learners.
文摘In this paper,we report the experience received from the project-based learning activity in a fundamental chemistry course.We involved the first year students in Faculty of Engineering at King Mongkut’s University of Technology Thonburi,Ratchaburi Learning Center,Thailand.This work considers the innovative activities performed in the field of chemistry and physics.This activity has been intensively implemented in teaching first year students.A project has been created to build up a small machine for measuring the concentration of sucrose solutions.The students participated in a project based learning(PBL)process,in which they worked in groups to create the instrument designed to measure the sucrose concentration in percentage by weight of sucrose in pure water solvent.Project-based learning has gained a greater position in the classroom as researchers have documented what teachers have long understood:Students become more engaged in learning when they have a chance to dig into complex and challenging problems that closely resemble real life.Moreover,several surveys have been conducted along one academic year to evaluate the impact of this method.The results of the surveys show that PBL encourages students’motivation and improves their knowledge involving the project.It is also pointed out that this methodology requires more dedication from lecturers than traditional methodology.
文摘Universities teach mainly specialized subjects and the liberal arts. Society expects university students to gain certain basic skills important when working for a company. These skills can be divided broadly into action, thinking, and teamwork. The purpose of this paper is to propose a method of project-based education for developing fundamental competencies for working persons. Many studies have been reported on educational methods with project management techniques, but few have considered project-based education aiming at improving fundamental competencies for working persons. If these competencies can be developed through project-based education, it will be possible to develop not only teamwork skills, but also a wide range of skills involving action as well as thinking. The traditional Japanese university curriculum comprises specialized subjects and the liberal arts. The author proposes the addition of project-based education to develop basic skills needed in the workforce. This research proposes an education model for basic competency training and examines the educational outcomes by studying results of a cooking tool project assigned to university students. The model includes Teoriya Resheniya Izobretatelskikh Zadatch （TRIZ, a Russian acronym for the theory of inventive problem solving）, a World Cafe, and the SECI process （a process of knowledge creation comprised of socialization, externalization, combination, and internalization in knowledge management） in the hope that this model will be conducive to implementing effective project-based learning. This research concludes that it is possible to develop the basic skills needed by university students in society through project-based learning under a basic skills education model.
文摘In this article, authors describe how to use the project-based learning （PBL） pedagogy to enhance students＇ Calculus learning based on the first author＇s experimental teaching experience. The ＂2014 BMCC Polar Art Calendar＂ project was completed by Calculus students at Borough of Manhattan Community College （BMCC） during the fall 2013 semester. Students were requested to apply graphs of polar equations to create computer-generated images with a variety of flower patterns by using the Maple technology in a math lab. At the end of this project, students were requested to submit and present their written reports to express their mathematical thinking. Authors also explain in details how to create projects compatible with textbook knowledge learning objectives, how to prepare scaffolding materials for students to use, how to utilize a math lab and to work with lab technicians in Maple Software, and how to design a rubric for project evaluations. Students＇ artwork created in the Polar Art Calendar are presented. Students＇ positive outcomes have proven a success of this project design as well as its execution as an example of PBL. Benefits to students and challenges to teachers on the use of PBL approach have been discussed at the end of this article.
文摘This thesis sketches the connotation of project-based learning and introduces the basis on which project-based learning is practiced and applied in school of software as well as the plan of further practicing project-based learning.At the same time,this thesis also discusses application of project-based learning in "education and cultivation plan of excellent engineer".
文摘All engineering students need to develop their important skills of leadership in project management. Many students have never been leaders in their social and school lives. A leading role is unimaginable to them and hence they cannot imagine how to achieve it. The purpose of this paper is to report a result of a new leadership education program which links a variety of simulated experiences with real actions of students in project based learning （PBL） to develop their leadership ability. The first step is for graduate students to gain knowledge in the leadership arena. Then, they utilize simulation to experience leadership actions many times. Simulation provides a safe environment in which they can try out many different approaches in taking leadership in various situations. In the next step, students as a team utilize PBL, so that the above simulated experiences can help them to actually take leadership. Students can apply trained leadership to actual projects. It is highly effective to apply conscious leadership to a project aimed at a specific goal in limited circumstances. This education repeats both of the steps above, raising leadership abilities in an upward spiral. In terms of students＇ evaluation of leadership education in project management, 360-degree assessments were carried out by teachers, senior, and junior students before and after the course, and authors compare their assessments thoroughly. As a result, authors are assured that students not only gained knowledge but also raised leadership abilities in their actions after this education. Six months after the time of leadership education employing simulated experiences and PBL, follow-up interviews were conducted on its effects. Authors recognized the cyclic period that students apply simulated experiences to PBL and that they seek different approaches in simulation for solving problems found in reality. This research concludes that this cycle of simulator and PBL can produce effective leadership actions.
文摘The Wavelet-Domain Projection Pursuit Learning Network (WDPPLN) is proposedfor restoring degraded image. The new network combines the advantages of both projectionpursuit and wavelet shrinkage. Restoring image is very difficult when little is known about apriori knowledge for multisource degraded factors. WDPPLN successfully resolves this problemby separately processing wavelet coefficients and scale coefficients. Parameters in WDPPLN,which are used to simulate degraded factors, are estimated via WDPPLN training, using scalecoefficients. Also, WDPPLN uses soft-threshold of wavelet shrinkage technique to suppress noisein three high frequency subbands. The new method is compared with the traditional methodsand the Projection Pursuit Learning Network (PPLN) method. Experimental results demonstratethat it is an effective method for unsupervised restoring degraded image.
文摘A growing number of studies are now emphasizing the critical importance of learning and knowledge accumulation for firm-level competitiveness. Despite the growing awareness, relatively fewer project-based firms have institutionalized mechanisms to systematically capture new project knowledge and re-use it to improve the execution of subsequent projects. The peculiarity of projects presents unique challenges that make the cognitive approach to learning difficult to implement. As such, researchers are recommending the social constructivist perspective of learning as the most viable strategy for cultivating learning within and across projects. However, scant work has been undertaken from this sociological perspective to analyze how temporary organizations manage knowledge arising from and relating to projects. From this standpoint, the aim of this paper is to discuss the learning mechanisms of construction firms. The study adopted a quantitative strategy by employing a questionnaire survey into the learning practices of construction projects in Ghana. Drawing on preliminary findings from the literature, the study proposes a model for cultivating learning within projects from the social constructivist viewpoint. In the model, project management practitioners can purposefully nurture or structure a project learning activity through four mechanisms <em>viz</em>.: <em>institutionalization, externalization, socialization and internalization</em>. The proposed model is subsequently validated in an empirical study into the learning practices during the implementation of construction projects in Ghana. Based on the empirical results, it seems that knowledge sharing and transfers through the four aforementioned learning mechanisms proposed by the model are highly regarded within project management practice in Ghana.
