In this study, we propose an incremental learning approach based on a machine-machine interaction via relative attribute feedbacks that exploit comparative relationships among top level image categories. One machine a...In this study, we propose an incremental learning approach based on a machine-machine interaction via relative attribute feedbacks that exploit comparative relationships among top level image categories. One machine acts as ＇Student （S）＇ with initially limited information and it endeavors to capture the task domain gradually by questioning its mentor on a pool of unlabeled data. The other machine is ＇Teacher （T）＇ with the implicit knowledge for helping S on learning the class models. T initiates relative attributes as a communication channel by randomly sorting the classes on attribute space in an unsupervised manner. S starts modeling the categories in this intermediate level by using only a limited number of labeled data. Thereafter, it first selects an entropy-based sample from the pool of unlabeled data and triggers the conversation by propagating the selected image with its belief class in a query. Since T already knows the ground truth labels, it not only decides whether the belief is true or false, but it also provides an attribute-based feedback to S in each case without revealing the true label of the query sample if the belief is false. So the number of training data is increased virtually by dropping the falsely predicted sample back into the unlabeled pool. Next, S updates the attribute space which, in fact, has an impact on T＇s future responses, and then the category models are updated concurrently for the next run. We experience the weakly supervised algorithm on the real world datasets of faces and natural scenes in comparison with direct attribute prediction and semi-supervised learning approaches, and a noteworthy performance increase is achieved.展开更多
This paper sets out to argue the relevance for translation studies of complexity theory. It endeavours to argue, though briefly, that translation can be conceptualized as an emergent concept. It then indicates how the...This paper sets out to argue the relevance for translation studies of complexity theory. It endeavours to argue, though briefly, that translation can be conceptualized as an emergent concept. It then indicates how theories of emergence in social studies provide new scope to theorise agency. Lastly, it considers the implications of the conceptualization for translator education. The arguments put forward in this paper lay the foundation for a philosophy of translation, i.e., a meta-theory of translation in which translation is viewed both as emerging from particular complex human interactions such as language and as being co-determined by complex contextual factors.展开更多
Flexible wearable sensors with excellent electric response and self-powered capability have become an appealing hotspot for personal healthcare and human-machine interfaces.Here,based on triboelectric nanogenerator(TE...Flexible wearable sensors with excellent electric response and self-powered capability have become an appealing hotspot for personal healthcare and human-machine interfaces.Here,based on triboelectric nanogenerator(TENG),a flexible self-powered tactile sensor composed of micro-frustum-arrays-structured polydimethylsiloxane(PDMS)film/copper(Cu)electrodes,and poly(vinylidenefluoride-trifluoroethylene)(P(VDF-TrFE))nanofibers has been demonstrated.The TENG-based self-powered tactile sensor can generate electrical signals through the contact-separation process of two triboelectric layers under external mechanical stimuli.Due to the uniform and controllable micro-frustum-arrays structure fabricated by micro-electro-mechanical system(MEMS)process and the P(VDF-TrFE)nanofibers fabricated by electrostatic spinning,the flexible PDMS-based sensor presents high sensitivity of 2.97 V kPa^-1,stability of 40,000 cycles(no significant decay),response time of 60 ms at 1 Hz,low detection pressure of a water drop(~4 Pa,35 mg)and good linearity of 0.99231 in low pressure region.Since the PDMS film presents ultra-flexibility and excellent-biocompatibility,the sensor can be comfortably attached on human body.Furthermore,the tactile sensor can recognize various types of human body movements by the corresponding electrical signals.Therefore,the as-prepared TENGs are potential on the prospects of gesture detection,health assessment,human-machine interfaces and so on.展开更多
文摘In this study, we propose an incremental learning approach based on a machine-machine interaction via relative attribute feedbacks that exploit comparative relationships among top level image categories. One machine acts as ＇Student （S）＇ with initially limited information and it endeavors to capture the task domain gradually by questioning its mentor on a pool of unlabeled data. The other machine is ＇Teacher （T）＇ with the implicit knowledge for helping S on learning the class models. T initiates relative attributes as a communication channel by randomly sorting the classes on attribute space in an unsupervised manner. S starts modeling the categories in this intermediate level by using only a limited number of labeled data. Thereafter, it first selects an entropy-based sample from the pool of unlabeled data and triggers the conversation by propagating the selected image with its belief class in a query. Since T already knows the ground truth labels, it not only decides whether the belief is true or false, but it also provides an attribute-based feedback to S in each case without revealing the true label of the query sample if the belief is false. So the number of training data is increased virtually by dropping the falsely predicted sample back into the unlabeled pool. Next, S updates the attribute space which, in fact, has an impact on T＇s future responses, and then the category models are updated concurrently for the next run. We experience the weakly supervised algorithm on the real world datasets of faces and natural scenes in comparison with direct attribute prediction and semi-supervised learning approaches, and a noteworthy performance increase is achieved.
文摘This paper sets out to argue the relevance for translation studies of complexity theory. It endeavours to argue, though briefly, that translation can be conceptualized as an emergent concept. It then indicates how theories of emergence in social studies provide new scope to theorise agency. Lastly, it considers the implications of the conceptualization for translator education. The arguments put forward in this paper lay the foundation for a philosophy of translation, i.e., a meta-theory of translation in which translation is viewed both as emerging from particular complex human interactions such as language and as being co-determined by complex contextual factors.
基金financially supported by the National Natural Science Foundation of China(51605449,51675493 and51705476)the National Key R&D Program of China(2018YFF0300605)+2 种基金Shanxi “1331 Project” Key Subject Construction(1331KSC)the Applied Fundamental Research Program of Shanxi Province(201601D021070)Zhangjiakou Science and Technology Research and Development Plan of Zhangjiakou City(1811009B-10)
文摘Flexible wearable sensors with excellent electric response and self-powered capability have become an appealing hotspot for personal healthcare and human-machine interfaces.Here,based on triboelectric nanogenerator(TENG),a flexible self-powered tactile sensor composed of micro-frustum-arrays-structured polydimethylsiloxane(PDMS)film/copper(Cu)electrodes,and poly(vinylidenefluoride-trifluoroethylene)(P(VDF-TrFE))nanofibers has been demonstrated.The TENG-based self-powered tactile sensor can generate electrical signals through the contact-separation process of two triboelectric layers under external mechanical stimuli.Due to the uniform and controllable micro-frustum-arrays structure fabricated by micro-electro-mechanical system(MEMS)process and the P(VDF-TrFE)nanofibers fabricated by electrostatic spinning,the flexible PDMS-based sensor presents high sensitivity of 2.97 V kPa^-1,stability of 40,000 cycles(no significant decay),response time of 60 ms at 1 Hz,low detection pressure of a water drop(~4 Pa,35 mg)and good linearity of 0.99231 in low pressure region.Since the PDMS film presents ultra-flexibility and excellent-biocompatibility,the sensor can be comfortably attached on human body.Furthermore,the tactile sensor can recognize various types of human body movements by the corresponding electrical signals.Therefore,the as-prepared TENGs are potential on the prospects of gesture detection,health assessment,human-machine interfaces and so on.
