Interference cancellation assisted lattice-reduction aided detection for MIMO systems

In this paper, we proposed and investigated the optimal successive interference cancellation (SIC) strategy designed for lattice-reduction-aided multiple-input multiple-output (MIMO) detectors. For the sake of generating the optimal MIMO symbol estimate at each SIC detection stage, we model the so-called effective symbols generated with the aid of lattice-reduction as joint Gaussian distributed random variables. However, after lattice-reduction, the effective symbols become correlated and exhibit a non-zero mean. Hence, we derive the optimal minimum-mean-squared-error (MMSE) SIC detector, which updates the mean and variance of the effective symbols at each SIC detection stage. As a result, the proposed detector achieves an approximately 3 dB Eb/N0 gain and performs close to the maximum likelihood detector

Asymmetry Parameter of the K1(1270,1400)K_{1} (1270, 1400) by Analyzing the B→K1ννˉB\to K_{1}\nu \bar{\nu} Transition Form Factors within QCD

Separating the mixture of the $K_{1}(1270)$ and $K_{1}(1400)$ states, the $B\to K_{1}(1270, 1400)\nu\bar{\nu}$ transition form factors are calculated in the three-point QCD sum rules approach. The longitudinal, transverse and total decay widths as well as the asymmetry parameter, characterizing the polarization of the axial $K_{1}(1270, 1400)$ and the branching ratio for these decays are evaluated.Comment: 25 pages, 3 figures, 3 table

Implementation Problems in the Development of Urban Community Services in the People\u27s Republic of China: The Case of Beijing

To review the ten year implementation of the community service policy of the People\u27s Republic of China, community service implementers and academics located in Beijing were interviewed. By employing implementation theories as a framework of analysis, a number of implementation problems are identified. In terms of policy characteristics and the structuring of implementation, this case shows that the objectives are not specific enough. The decentralized implementation strategy allows the implementers too much discretionary power. The shortage of qualified and motivated personnel further complicate the issue. Lastly, the policy environment of Beijing does not lend adequate support to the policy

The Challenge of Open: Empowering Students or Eroding Privacy?

Open education can mean different things to different people. A term which frequently refers to the creation, sharing and usage of open educational resources, open education can also refer to the use of technologies which promote collaborative, flexible learning and sharing of teaching practices, thus providing new opportunities for enhancing teaching and learning and assessment practices (Cape Town Open Education Declaration, 2007). Within this context, open education is often promoted as a means of widening access to education, improving equity and enhancing the student learning experience (Creelman, Cronin and Weller 2018). However in an increasingly privacy-conscious era, where data breaches are commonly reported and surveillance practices are accepted as part of the open web, it could also be argued that open practice feeds “data capitalism” (Myers-West 2017), eroding student and educator privacy in the process. This highly reflective and evaluative panel presentation will explore existing and emerging concerns, challenges and associated privacy and ethical issues surrounding open education in an era of big data. In doing so, this panel presentation aligns with theme 1 of OER19, “Back to Basics”, exploring difficult questions such as open for whom? Whose interests are served by the open agenda and what are the implications for educators, students and for our higher education institutions

Developing all learners through analytics: a collaborative consultative approach to professional development and support

By the end of this session, delegates will be able to: -explore the potential value of learning analytics for creating a supportive educational experience for students and for increasing students’ feelings of ownership, agency and self-regulation. -examine the role of professional development resources and support in increasing staff and student digital proficiencies in using learning data and in facilitating greater evidence-based decision-making in HE. -identify how we can collaborate with our institutional colleagues and our students in the design and provision of professional development resources and support in relation to the analysis and interpretation of learning data to support student success. -consider staff, students and sectoral perspectives on the issues, challenges, potential uses and concerns surrounding the use of learning data to support students in H