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Gaze target detection in the video aims to localize the gaze target in each video frame. The person gazes at different targets at different times. In the transition segment from one gaze target to gaze at another, the person may not gaze at a specific target. The gaze target detection method with an image transformer neglects to consider the temporal transition segment. The gaze direction in the transition segment may hinder the gaze target detection in the video. For gaze target detection in video, this paper proposes a gaze transition-based model, which contains a gaze direction guidance module, and a gaze transition temporal fusion module. In the gaze direction guidance module, the position of the gaze target is used to learn the heatmap of the gaze direction. The gaze target is detected by guiding with the heatmap of the gaze direction, which can suppress the target out of the gaze direction and predict the accurate position of the gaze target. In the gaze transition temporal fusion module, the heatmap in multiple frames forms the spatial-temporal heatmap. To learn the changes in the spatial-temporal heatmap, this paper uses bi-directional spatial-temporal convolution long short-term memory (LSTM), which can extract the memory-based spatial-temporal heatmap. The gaze transition is described by introducing the Gaussian-based temporal model. To localize the temporal segment of the gaze transition with uncertainty temporal length, this paper designs a Gaussian-based temporal fusion method, which can estimate the gaze transition with the start timestamp, the end timestamp, and the temporal length. By localizing the gaze transition segment, the transition effect can be removed for gaze target detection. Gaze transition- based model is trained with gaze direction- based loss, gaze target existence loss, gaze target heatmap loss, and gaze transition temporal localization loss. In the GazeFollow dataset and VideoAttentionTarget dataset, the experimental results show that the gaze transition-based model outperforms the image transformer-based model for gaze target detection in video. [ABSTRACT FROM AUTHOR]

Copyright of Modern Educational Technology is the property of Editorial Board of Modern Educational Technology, Tsinghua University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Digital Education is the property of Haiyan Publishing Co. Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Research in Education Sciences is the property of National Taiwan Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Based on the learning characteristics of the higher quality professional farmer students, this article had taken the course of production technology and equipment of facility agriculture as an example, which was one of the core curriculum of the major of facility agriculture of Beijing Vocational College of Agriculture. The course teaching overall plan was elaborated in this paper in terms of teaching objectives, course content, teaching mode, curriculum politics and assessment program. Also, with the teaching implementation process analysis of the learning module task of installation and operation of soilless culture facilities, the teaching exploration and practice of the teaching team for this course was displayed in the paper, which provided profitable experience and reference for the deeper curriculum reform. [ABSTRACT FROM AUTHOR]

Copyright of Digital Education is the property of Haiyan Publishing Co. Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With inherent sparse spike-based coding and asynchronous event-driven computation, spiking neural network (SNN) is naturally suitable for processing event stream data of event cameras. In order to improve the feature extraction and classification performance of bio-inspired hierarchical SNNs, in this paper an event camera object recognition system based on biological synaptic plasticity is proposed. In our system input event streams were firstly segmented adaptively using spiking neuron potential to improve computational efficiency of the system. Multi-layer feature learning and classification are implemented by our bio-inspired hierarchical SNN with synaptic plasticity. After Gabor filter-based event-driven convolution layer which extracted primary visual features of event streams, we used a feature learning layer with unsupervised spiking timing dependent plasticity (STDP) rule to help the network extract frequent salient features, and a feature learning layer with reward-modulated STDP rule to help the network learn diagnostic features. The classification accuracies of the network proposed in this paper on the four benchmark event stream datasets were better than the existing bio-inspired hierarchical SNNs. Moreover, our method showed good classification ability for short event stream input data, and was robust to input event stream noise. The results show that our method can improve the feature extraction and classification performance of this kind of SNNs for event camera object recognition.

Comparing the similarity of different enhancements of the same image is the key to achieving remarkable results in contrastive learning. The traditional contrastive learning method uses two different views of the image. In order to learn more information of the image to improve the classification accuracy, based on MoCo, this paper presented multi-view momentum contrast learning algorithms. In each iteration, this paper used a query encoder and multiple momentum encoders to extract feature for multiple data enhancements of the image, so that it could use more data enhancements and negative samples in this iteration. And it used the optimized noise contrast estimation(InfoNCE) to calculate the loss, so that the query encoder could obtain feature representations which was more beneficial to downstream tasks. The query encoder network updated with gradient backhaul, and each momentum encoder updated with an improved momentum update formula to improve the generalization ability of the model. Experimental results show that using multi-view momentum contrastive learning can effectively improve the classification accuracy of the model. [ABSTRACT FROM AUTHOR]

According to the subject characteristics of structural chemistry and the learning situation of undergraduates in Qufu Normal University, this paper explores the teaching reform to eliminate students' fear of difficulties and cultivate their interest in the subject. It is considered that designing a reasonable and interesting introduction course is an effective measure. The high-quality teaching effect and scientific thinking mode can be achieved by using the analogy method, reducing complexity to simplicity, and clarifying the scope, degree, logic and meaning of structural chemistry learning. [ABSTRACT FROM AUTHOR]

Copyright of Architectural Journal / Jian Zhu Xue Bao is the property of Architectural Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Architectural Journal / Jian Zhu Xue Bao is the property of Architectural Journal Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Hubei Open Vocational College is the property of Journal of Hubei Open Vocational College Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Transcranial magnetic stimulation (TMS) as a noninvasive neuromodulation technique can improve the impairment of learning and memory caused by diseases, and the regulation of learning and memory depends on synaptic plasticity. TMS can affect plasticity of brain synaptic. This paper reviews the effects of TMS on synaptic plasticity from two aspects of structural and functional plasticity, and further reveals the mechanism of TMS from synaptic vesicles, neurotransmitters, synaptic associated proteins, brain derived neurotrophic factor and related pathways. Finally, it is found that TMS could affect neuronal morphology, glutamate receptor and neurotransmitter, and regulate the expression of synaptic associated proteins through the expression of brain derived neurotrophic factor, thus affecting the learning and memory function. This paper reviews the effects of TMS on learning, memory and plasticity of brain synaptic, which provides a reference for the study of the mechanism of TMS.

Molecular biology theory and technology, as a frontier subject of life sciences, are developing rapidly. As the key link between theory and practice, molecular biology experimental courses play an important role in the cultivation of students' critical thinking and innovation abilities. This paper analyzed the critical issues in experimental teaching by collecting and reflecting on students' feedbacks. With a focus on the Empowerment and Efficiency Oriented Teaching, the study was aimed at improving students' hands-on and thinking ability, and raising the efficacy of education. A series of measures were taken in attempts to renew the setting of teaching content and reconstruct the classroom timing allotment. The reform of the teaching scheme not only significantly increases students' understanding and mastery of knowledge, and empowers students with stronger thinking and learning abilities, but also enhances the teaching efficacy of experimental courses and further improves students' scientific literacy.

Background: Team-Based Learning (TBL) is a potentially effective method of instruction that has been applied only infrequently in nursing education in Taiwan., Purpose: This study was developed to examine the effects of incorporating the TBL strategy into the course "Advanced Medical Nursing English"., Methods: A quasi-experimental, single group, and pre-post test design was adopted. Nursing students who took the "Advanced Medical Nursing English" elective course used the TBL strategy for 8-weeks. Students were assigned to heterogenic groups of 12 students each based on their scores on an English pre-test. The collected data included the scores on individual and group readiness tests, a self-directed learning questionnaire, learning satisfaction, and an English posttest. Self-completed reflection papers and focused group interviews were used for qualitative appraisal., Results: A total of 72 students were enrolled. Nearly all (93.1%) were female and 21-22 years of age. The results of a paired samples t-test applied to examine the effects of the TBL strategy on learning outcomes showed that English posttest and self-directed learning ability scores had both improved significantly (all p < .05). The results of ANOVA tests showed that students with lower pre-test scores improved more than those with higher pre-test scores. The results of a sample t-test with a test value of 4.0 applied to examine learning satisfaction found a non-significant change (p > .05), indicating no change in perceived satisfaction. The qualitative analysis identified four themes regarding perceptions of the TBL strategy, including "friendships in learning", "harmonious atmosphere and participations", "inertial shock and adjustments", and " excessive learning load"., Conclusions: TBL was shown to be an effective learning strategy for RN-BSN students in a Medical Nursing English Course, particularly those with relatively low pre-test scores. Future studies should focus attention on reading assignments to avoid overburdening students. The results of this study may serve as a reference for medical nursing English education.

Copyright of Journal of Education Research (1680-6360) is the property of Angle Publishing Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Anomaly detection aims to capture the discriminative features with limited training samples. However, when some anomalies share common compositional patterns with the normal training data, the model likely reconstructs the anomalies well, leading to the miss detection of anomalies. To mitigate this drawback, this paper proposed a novel contrastive memory network, which used the contrast learning framework to separate the sample features based on the autoencoder, and then designed a memory network to suppress the normal features similar to anomaly. This method proposed a two-stage framework for detecting abnormal events. In the first stage, the method used contrastive learning to increase the difference between normal features and abnormal features, and gained representation to be the augment memory and suppression memory of memory network. In the second stage, the model used augment memory to record multi-time normal behavior features, and used suppression memory to constrain the expression of pseudo anomaly items in the augment memory. The AUC value reached 83. 26% on UCF Crime datasets and 87.53% on Shanghai Tech datasets, which were 1. 14% and 2.43% higher than the existing methods. The results demonstrate that this method can efficiently predict the temporal localization of anomaly events. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Academic Library & Information Science is the property of Anhui University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Education Research (1680-6360) is the property of Angle Publishing Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The prevalence of “water courses” and the lack of “genuine learning” among students in college classrooms had sparked popular research on “golden lessons” and theirconstructions. Making use ofbibliometric tools, this paper quantitatively analyzed the research literature on “golden courses” and their development, including the quantity and temporal distribution of studies, the quality and distribution of journals, as well as the distribution of authors and citations. The research founding indicated that, although the quantity of literature about golden lesson grown quickly and the ratio of golden lesson construction to itclimbed smoothly, the overall quality still remained low and the authorswere scattered. Further spectrographic analysis showed that the researchconducted at the macro level, such as curriculum development and teaching reforms, was the mainstream in this field. Studies at the meso level, concerning the subjects and methods of “golden course” development, followed next. While research at the micro level, such as specific development plans and course selection, was scarce. Attention was expected to be given to the study of the “internalization” and “supporting measures” of “quality course” development. [ABSTRACT FROM AUTHOR]

Unsupervised commonsense question answering is a question answering model that uses the machine to automatically generate question-answering data. There are some problems in the question-answering data generated by current methods, such as noise data and random difficulty of questions. This paper proposed an unsupervised commonsense question-answering model based on curriculum learning. Firstly, it generated a question-answering dataset according to knowledge, then evaluated the diversity and fluency of the question answering dataset, and filtered the data by combining the two evaluation results to remove noise data. Finally, according to the course learning strategy, it used the similarity between the interference item and the correct answer as the difficulty evaluation standard to train the model according to the difficulty level. The accuracy of the test tasks is improved by 1.5%～3.5%, which proves that the model is effective in unsupervised commonsense question-answering tasks. [ABSTRACT FROM AUTHOR]

Unsupervised commonsense question answering is a question answering model that uses the machine to automatically generate question-answering data. There are some problems in the question-answering data generated by current methods, such as noise data and random difficulty of questions. This paper proposed an unsupervised commonsense question-answering model based on curriculum learning. Firstly, it generated a question-answering dataset according to knowledge, then evaluated the diversity and fluency of the question answering dataset, and filtered the data by combining the two evaluation results to remove noise data. Finally, according to the course learning strategy, it used the similarity between the interference item and the correct answer as the difficulty evaluation standard to train the model according to the difficulty level. The accuracy of the test tasks is improved by 1.5%～3.5%, which proves that the model is effective in unsupervised commonsense question-answering tasks. [ABSTRACT FROM AUTHOR]

In Paul Willis’s “Learning to Labour”, the lads articulate ‘anti-school culture’ as their reaction after penetrating/seeing through the schooling mechanism. This paper will demonstrate some other reactions to seeing through the school system, through the case of migrant workers in Shenzhen China. These reactions are: bypass, repair, and “mobile learning”. By analyzing the learning strategies displayed by a group of young migrant workers in an electronics factory, who left school out of choice but were keen to learn, this paper argues that “mobile learning” allows social actors to imagine and realize new possibilities without challenging the existing structure. Migrant workers use this method to bypass and repair the school system which is falling apart. This paper points out that migrant workers who drop out from school are not “bad students.” This label is not helpful for understanding their situation or for solving their problems. Their problems cannot be solved by exhausting various resources to help them become “good students.” These young migrant workers are not backward, unteachable, unmotivated, or unwilling to learn. Rather, they saw through the middleclass nature of schooling and its urban bias, and realized it cannot possibly help them improve their livelihoods. They become wage labourers in factories in Shenzhen as the result of finding alternatives. Migrant workers who engage in “mobile learning” move to different places and social contexts. On the one hand, through “legitimate peripheral participation,” they gain knowledge and skills in that social context, and they collate and assemble such learning resources for their own use. On the other hand, they mobilize cultural taste, social experiences, and symbols between urban and rural settings, and thus create social, cultural, and symbolic capital which enables them to transform their subjectivities in response to the failure of the schooling system. However, “mobile learning” has its limitations. All the resources, opportunities, and every transition of this learning process is not institutionalized. “Mobile learning” relies largely on waiting, coincidences, the appreciation of supervisors and workers’ own extra labor (such as showing loyalty, hard work, diligence, etc.). In short, the path of migrant workers’ “mobile learning” is thin and easily ruptured. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Education Research (1680-6360) is the property of Angle Publishing Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The deep decision tree migration learning boosting method ( DtrBoost) can effectively realize the migration learning from a single source domain to a target domain under supervision, but can not realize the unsupervised migration scenario under multiple source domains. To solve this problem, this paper proposed an unsupervised transfer learning boosting method for optimizing the weight under multi-source domain distribution. The main idea was to calculate the corresponding KL value according to the distribution of different source domains and target domains, selected an appropriate number of samples from different source domains to train the classifier and pseudo label the samples from the target domain. Finally, the algorithm assigned different learning weights according to the KL distance of each different source domain, and the labeled source domain samples integrated to the pseudo labeled target domain to obtain the final result. Comparative experiments show that the proposed algorithm achieves better classification accuracy and adaptive effect on different data sets. The average classification error rate decreases by 2. 4% and more than 6% on the best marketing data set. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Frontiers of Computer Science & Technology is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Research in Education Sciences is the property of National Taiwan Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Research in Education Sciences is the property of National Taiwan Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Frontiers of Computer Science & Technology is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Technology & Chinese Language Teaching is the property of Middle Tennessee State University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Fuzzy clustering is an important research content in the fields of pattern recognition, machine learning and image processing. Fuzzy C-means clustering algorithm is the most commonly used fuzzy clustering algorithm. The algorithm needs to preset the number of clusters in order to cluster the data set. This paper proposed a new clustering validity index to validate the clustering results. This index defined the three important features of compactness, resolution and overlap degree from the perspective of partition entropy, membership degree and geometric structure. On this basis, this paper proposed a method of determining the optimal clustering number. It validated the new clustering validity index and the traditional effectiveness index in six artificial data sets and three real data sets. The experimental results show that the proposed indexes and methods can effectively evaluate the clustering results and are suitable for determining the optimal clustering number of the samples. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In 2001, Hong Kong started an enormous, comprehensive, and highly impacted curriculum reform through introducing the "Learning to learn". This reform incorporated changes in subject structure, integration of knowledge and skill, four key tasks, learning and teaching strategies, learning assessment approaches and provision of additional teaching resources. It is regarded as the largest curriculum reform in scale in history of Hong Kong. In 2005, the Education Bureau further reformed the educational system and its curriculum structure, which aimed to transform student learning. These changes included multiple pathways for students, further education, broad and balanced curriculum, integration of academic knowledge and application, and shifting from examination orientation to multiple assessments. However, this reform faced challenges in its design and existed deficits in its implementation. It is being criticized that the curriculum implementation missed the essence of its design. This paper aims to discuss the Hong Kong curriculum reform since 2005. First, it highlights the curriculum reform initiatives and their rationales in New Senior Secondary (NSS) education. Second, it inquires into the implementation dip of the rationales and implementation of NSS reform. Finally, it discusses the unchanged essence of NSS reform. In precise, this article exhibits the significant changes in this new reform such as educational system, subject structure, and curriculum choices. However, it stresses that the reform has not yet changed some fundamental issues such as examination oriented culture and student diversity. [ABSTRACT FROM AUTHOR]

Copyright of Forensic Science & Technology is the property of Institute of Forensic Science, Ministry of Public Security and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Clean Coal Technology is the property of Clean Coal Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Research in Education Sciences is the property of National Taiwan Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the scene of document verification，the standard deep learning face recognition method has low accuracy and poor real-time performance on embedded devices. To solve these problems，this paper proposes a modified efficient convolutional neural network（CNN）called Lightnet and adopts the transfer learning method. Lightnet is an efficient CNN module composed of depthwise separable convolution，linear bottleneck structure and attention module. After introducing the loss function AM-Softmax with additive angle margin， the network model can effectively solve the problems of redundancy parameter and vast calculation for standard CNN in the foundation of ensuring the high accuracy of face recognition. The transfer learning method can enhance the scene-identity face matching performance by freezing all the convolution layer weights of the pre-trained model and fine-tuning training in the self-made scene-identity face matching dataset. The experimental results show that the designed efficient scene-identity face matching algorithm has achieved good results in terms of verification accuracy，parameters and verification speed，and has good robustness in life scenarios. [ABSTRACT FROM AUTHOR]

Copyright of Chung Cheng Educational Studies is the property of Chung Cheng University, College of Education and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the problem of the computational complexity and low segmentation precision of the multi-threshold image segmentation method, this paper proposed an ISCA based multi-threshold image segmentation method. Firstly, this method used a chaotic initialization technique to improve the quality of initial population. Secondly, it introduced an adaptive strategy to adjust the parameters according to the fitness values. Finally, it utilized an opposition-based learning strategy, then selected the better particles. The results of the Berkeley image and the plant canopy image segmentation experiments show that this method has a satisfied performance in terms of running time and segmentation accuracy. And it has a strong robustness. [ABSTRACT FROM AUTHOR]

Adaptive governance is a new choice to solve the problem of water resource governance which caused by the increasing complexity and uncertainty. It offers a great feasible approach with the learning-capacity to settle issues caused by climate change, etc. This paper proposed the experience-weighted attraction (EWA) transformational learning based on the EWA learning theory, social learning theory and behavioral game theory. The EWA transformational learning has characteristics of multi-level and triple loop characters to promote the knowledge sharing and communication between individuals. Meanwhile, the paper analyzed the factors which may affect the human behavior pattern by system dynamics. Then, the paper modeled the dynamic system of water transfer in Hami region to analyze the law of the human behavior pattern, identify the key factors which affected human decision-making, and offer the plan for policy adjustment. The outcome of simulation proved that the learning rule of adaptive governance could improve the effective and the continuity of water transfer. [ABSTRACT FROM AUTHOR]

With the quick increase of new knowledge in genetics, undergraduate teaching of genetics is becoming a challenge for many teachers. In this paper, the author suggested that it would be important to construct the knowledge network of genetics and to develop the self-learning ability of students. This could help students to read textbooks "from the thicker to the thinner in classroom" and "from the thinner to the thicker outside classroom", so that students would turn to be the talents with new ideas and have more competent ability in biology-related fields.

With the rapid pace of development and reform in education learners face many challenges. Learning how to acquire skills and how to think are very important issues. The application of mind mapping can help students to enhance the creative thinking and problem-solving abilities of the whole brain. In other words, mind-mapping is a visual or pictorial thinking method. This paper introduces the basic concept of mind-mapping, radiant thinking, the methods of mind-mapping, its rules of application, and examples of such application, to improve understanding and knowledge about mind-mapping.

To explore the new progress of the experimental study of traditional Chinese medicine in the treatment of vascular. Consulted the relevant papers and integrated the elementary theory, we summarized the virtue of Chinese medicine in the treatment of vascular dementia and insufficient and future development of the experimental study of it. It was confirmed that the traditional Chinese medicine has a lot of target spots in the brain and less ill-effect, it could ameliorate several phenotypes of pathophysiology of vascular dementia and improve the ability of learning and memory of animals with vascular dementia.

Based on the pharmacological research of Chinese herbs on AD and some famous hypothesis on AD, such as dysfunction of nervous transmitter metabolism, apoptosis, inflammation etc, we consulted and analyzed relevant papers. We found the effective mechanism of Ginsenoside, Osthol, Rhodosin, and (-) Clausenamide were related to many pathological channels of AD, and Ginsenoside had effect on many pathological channels. The results have provided some clues for selecting effective herbs on AD.

Copyright of Journal of Image & Graphics is the property of Editorial Office of Journal of Image & Graphics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Engineering training is an extremely important practical course for the innovative talents cultivation of all disciplines. Aiming at the problems existing in engineering training, such as loose connection with engineering practice, lack of process assessment and weak quality consciousness. This paper proposes engineering ability-oriented practice teaching reform, teaching objective and teaching project are set up according to the ability certification standards. Guided by a comprehensive industrial project, industrial products are adopted instead of standard teaching aids. Teaching content is adjusted according to the theory of "the zone of proximal development", students are guided to explore learning. Full-process control, the student score is evaluated by combining formative assessment with summative assessment. Using spiral propulsion triangle cycle of self-evaluation, peer-evaluation, teaching evaluation, form a positive interaction to promote teaching. Emphasize detail, fine work, students are encouraged to be artisans . Research shows that by establishing a real and complete industrial environment, assessing the learning process, mutual evaluation and interaction, students learning enthusiasm is effectively stimulated, students problem-solving ability and system thinking have been improved. They pursue the highest quality, quality of awareness and artisan spirit have been enhanced . [ABSTRACT FROM AUTHOR]

In this paper, a perforating mold with complex geometric parameters was fabricated by 3D printing technology, then a waxy perforating core was fabricated, and finally the core is placed in a sample mold to pour concrete samples. The results show that the complex wellbore fabricated by this method has high dimensional accuracy, and the perforation holes after dewaxing are clean. These features ensure the consistency of the physical model and the numerical analysis model to a certain extent, which provides experimental verification for the theoretical model. The application of 3D printing technology in experimental teaching simplifies the process of the establishment of the complex physical models, and avoids the weakening of students’ learning enthusiasm caused by the interruption of learning process, and effectively stimulates students'awareness of exploration and innovation. [ABSTRACT FROM AUTHOR]