Ethnic identity and acculturation : a sociocultural perspective on peer editing in ESL writing.

In this dissertation, peer editing as one pedagogical practice in ESL writing is studied from a sociocultural perspective. Such a perspective has been neglected in the previous research in the field. In this study, the theories of the self, the ethnic identity and the acculturation are examined and an ethnographic study reported. The study suggests that pedagogical practices such as peer editing in ESL writing are also sociocultural practices. We cannot fully understand ESL teaching and learning if we ignore the sociocultural aspects and concentrate only on linguistic, psychological, and cognitive aspects. Using Mead, Bakhtin, Freire, and MacIntyre\u27s theories, I have constructed a theoretical framework for my research in critique of the previous sociocultural theories on ESL acquisition. This theoretical framework has three interrelated components: a non-essentialist theory of the self, a non-ethnocentrist theory of ethnic identity, and a theory of acculturation as pluralistic cultural coexistence and amalgamation. Of these three components, the most important is the constructing and ever changing of a person\u27s ethnic identity, which in turn could have a strong impact on transforming the social world. My ethnographic study, which has been conducted in four ESL writing classes in a college on the West Coast, suggests that students\u27 interaction in peer editing helps students enact their ethnic identity and acculturate into the multicultural American society. Telling and retelling their stories in peer editing, student writers and readers reach out to each other as narrative selves and narrative others. Together, they use the stories to give their life-world meaning. Peer editing not only could help students understand their past and present, but could also help them to choose the actions they want to take to transform themselves and their life-world

LL-fuzzy ideal degrees in effect algebras

summary:In this paper, considering $L$ being a completely distributive lattice, we first introduce the concept of $L$-fuzzy ideal degrees in an effect algebra $E$, in symbol $\mathfrak{D}_{ei}$. Further, we characterize $L$-fuzzy ideal degrees by cut sets. Then it is shown that an $L$-fuzzy subset $A$ in $E$ is an $L$-fuzzy ideal if and only if $\mathfrak{D}_{ei}(A)=\top,$ which can be seen as a generalization of fuzzy ideals. Later, we discuss the relations between $L$-fuzzy ideals and cut sets ($L_{\beta}$-nested sets and $L_{\alpha}$-nested sets). Finally, we obtain that the $L$-fuzzy ideal degree is an $(L,L)$-fuzzy convexity. The morphism between two effect algebras is an $(L,L)$-fuzzy convexity-preserving mapping

Load reduction of a monopile wind turbine tower using optimal tuned mass dampers

We investigate to apply tuned mass dampers (TMDs) (one in the fore–aft direction, one in the side– side direction) to suppress the vibration of a monopile wind turbine tower. Using the spectral element method, we derive a finite-dimensional state-space model d from an infinite-dimensional model d of a monopile wind turbine tower stabilised by a TMD located in the nacelle. and d can be used to represent the dynamics of the tower and TMD in either the fore–aft direction or the side– side direction. The wind turbine tower subsystem of is modelled as a non-uniform SCOLE (NASA Spacecraft Control Laboratory Experiment) system consisting of an Euler–Bernoulli beam equation describing the dynamics of the flexible tower and the Newton–Euler rigid body equations describing the dynamics of the heavy rotor-nacelle assembly (RNA) by neglecting any coupling with blade motions. d can be used for fast and accurate simulation for the dynamics of the wind turbine tower as well as for optimal TMD designs. We show that d agrees very well with the FAST (fatigue, aerodynamics, structures and turbulence) simulation of the NREL 5-MW wind turbine model. We optimise the parameters of the TMD by minimising the frequency-limited H2-norm of the transfer function matrix of d which has input of force and torque acting on the RNA, and output of tower-top displacement. The performances of the optimal TMDs in the fore–aft and side–side directions are tested through FAST simulations, which achieve substantial fatigue load reductions. This research also demonstrates how to optimally tune TMDs to reduce vibrations of flexible structures described by partial differential equations

Theory-driven Bilateral Dynamic Preference Learning for Person and Job Match: A Process-oriented Multi-step Multi-objective Method

Person-job matching is a typical dynamic process with bilateral interactions between job seekers and jobs, along with sample imbalance issues. These characteristics pose significant challenges when designing an intelligent person-job match method. In this paper, we propose a novel process-oriented view of the person-job matching problem and formulate it as a multi-step multi-objective bilateral match learning problem. Our method combines profile features and historical sequential behaviors to learn the bilateral attributes and dynamic preferences, with multimodal data integrated through various attention mechanisms, such as the orthogonal multi-head and gated mechanisms. The method includes a sequence update module to learn the bilateral preferences and their updates sensitive to feedback. Furthermore, the multi-step constraint effectively solves the problem of imbalanced samples through partial relationships and information transmission between multi-objectives. Abundant experiments show that our method outperforms state-of-the-art methods in providing successful matches and improving recruitment efficiency