372 research outputs found
Corpus-Based Critical Discourse Analysis of Women’s Representation in Shen Bao (1872-1949) and People’s Daily (1950-2012)
This thesis aims to explore and analyse women’s representations in Shen Bao (1872-1949) and
People’s Daily (1950-2012) in China over a period of 140 years (1872-2012). Combining the
quantitative corpus analysis of 1.9 million words of data with qualitative analyses using critical
discourse analysis (CDA), it examines four distinctive historical eras in the press portrayal of
women: late imperial Qing (1872–1911), Republican (1912–1949), socialist (1950-1978) and
the post-socialist (1979-2012). During these 140 years, China experienced dramatic sociocultural shifts and political transformations under the guidance of different ideologies over this
crucial historical time. Women were placed right in the centre of this turmoil, and women’s
roles have continuously been renewed, recreated, defended and modified (Williams, 1977).
Women were deemed inferior to men were nothing more than the result of social constructions.
Women’s representations are embedded in ideological frameworks supported by existing
power relations in the patriarchal society. They operated in the symbolic world through
discursive construction that defines women in ways that shape the social understanding of their
role, status and identities. This construction of women by the dominant forces in society serves
to sustain the existing patriarchal power relations. The thesis focuses on newspapers because
of its central role in shaping public opinions, setting agendas, and maintaining power structure
Broadsheet newspapers have the power to define key issues, topics, and situations which gives
them ideological power.
CDA pays attention to both the macro-level of context through a top-down approach, and the
micro-level by analysing how ideologies, dominance and power relations are expressed in
language. In contrast, Corpus Linguistics (CL) deals with large amounts of text by providing
detailed information of the micro-level. CL is basically a bottom-up approach, allowing the
data generated in a corpus to take the lead, and thereby limits bias. The data generated by
corpus analytical tools in CL is not handpicked data selected by the analyst, it is typical and
representative linguistic patterns that have been extracted from a large amount of data.
Women’s representations have undergone significant transformations across the four historical
eras in China as some women gain more economic independence and could challenge the
power hierarchies. In the late Qing era, women were not described as the opposite gender of
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men, but are represented as the weak, incompetent, decadent, and pathological symbol of premodernity in Shen Bao. Articles in Shen Bao promoted representations of women as “Mothers
of the Nation” and “Heroines”, which are variations of traditional “good wife and mother” and
“devoted to husband and son” sugar-coated with modern nationalism. In the socialist era,
women were mostly represented as strong, masculine, selfless, and ideologically correct
workers in the labour force, and as emotionally and physically the same as men. Women lived
and breathed for the state, and were willing to devote their lives, youth and efforts to
communism and socialism. In the post-socialist era, women’s representations in the People’s
Daily are more diverse. Discourses on women throughout the 140 years acted as a tool to
legitimize various national agendas.
This study offers empirical evidence and provides a macro level picture of the transformation
of women’s representations in the 140 years of history, underpinning the drive behind; also a
micro level analysis of detailed discussion on the confliction and consistencies of women
discourse over the four historical eras. Women’s studies have their origin outside of China, in
the west. I hope this study will shed some light onto the many components of the scarcely
researched localization of west women theories into Chinese terms, which I believe is the next
important issue and the next biggest challenge in women’s studies in China
Machine learning for fiber nonlinearity mitigation in long-haul coherent optical transmission systems
Fiber nonlinearities from Kerr effect are considered as major constraints for enhancing the transmission capacity in current optical transmission systems. Digital nonlinearity compensation techniques such as digital backpropagation can perform well but require high computing resources. Machine learning can provide a low complexity capability especially for high-dimensional classification problems. Recently several supervised and unsupervised machine learning techniques have been investigated in the field of fiber nonlinearity mitigation. This paper offers a brief review of the principles, performance and complexity of these machine learning approaches in the application of nonlinearity mitigation
Digital Signal Processing for Optical Communications and Networks
The achievable information rates of optical communication networks have been widely increased over the past four decades with the introduction and development of optical amplifiers, coherent detection, advanced modulation formats, and digital signal processing techniques. These developments promoted the revolution of optical communication systems and the growth of Internet, towards the direction of high-capacity and long-distance transmissions. The performance of long-haul high-capacity optical fiber communication systems is significantly degraded by transmission impairments, such as chromatic dispersion, polarization mode dispersion, laser phase noise and Kerr fiber nonlinearities. With the entire capture of the amplitude and phase of the signals using coherent optical detection, the powerful compensation and effective mitigation of the transmission impairments can be implemented using the digital signal processing in electrical domain. This becomes one of the most promising techniques for next-generation optical communication networks to achieve a performance close to the Shannon capacity limit. This chapter will focus on the introduction and investigation of digital signal processing employed for channel impairments compensation based on the coherent detection of optical signals, to provide a roadmap for the design and implementation of real-time optical fiber communication systems
Ideal magnetic dipole scattering
We introduce the concept of tunable ideal magnetic dipole scattering, where a
nonmagnetic nanoparticle scatters lights as a pure magnetic dipole. High
refractive index subwavelength nanoparticles usually support both electric and
magnetic dipole responses. Thus, to achieve ideal magnetic dipole scattering
one has to suppress the electric dipole response. Such a possibility was
recently demonstrated for the so-called anapole mode, which is associated with
zero electric dipole scattering. By overlapping magnetic dipole resonance with
the anapole mode we achieve ideal magnetic dipole scattering in the far-field
with tunable high scattering resonances in near infrared spectrum. We
demonstrate that such condition can be realized for two subwavelength
geometries. One of them is core-shell nanosphere consisting of Au core and
silicon shell. It can be also achieved in other geometries, including
nanodisks, which are compatible with current nanofabrication technology.Comment: Submit for publication, comments are welcom
Isotropic Magnetic Purcell Effect
Manipulating the spontaneous emission rate of optical emitters with
all-dielectric nanoparticles benefits from their low-loss nature and thus
provides relatively large extrinsic quantum yield. However, such Purcell effect
greatly depends on the orientation of the dipole emitter. Here, we introduce
the concept of isotropic magnetic Purcell effect with Purcell factors about 300
and large extrinsic quantum yield (more than 80%) for a magnetic dipole emitter
of arbitrary orientation in an asymmetric silicon nanocavity. The extrinsic
quantum yield can be even boosted up to nearly 100% by utilizing a GaP
nanocavity. Isotropy of the Purcell factor is manifested via the
orientation-independent emission of the magnetic dipole source. This isotropic
Purcell effect is robust against small displacement of emitter on the order of
10 nm, releasing the requirement of precise alignment in experiments.Comment: 18 pages, 5 figure
Non-orthogonal signal transmission over nonlinear optical channels
The performance of spectrally efficient frequency division multiplexing (SEFDM) in optical communication systems is investigated considering the impact of fiber nonlinearities. Relative to orthogonal frequency division multiplexing (OFDM), sub-carriers within SEFDM signals are packed closer at a frequency spacing less than the symbol rate. In order to recover the data, a specially designed sphere decoding detector is used at the receiver end to compensate for the self-created inter carrier interference encountered in SEFDM signals. Our research demonstrated the benefits of the use of sphere decoding in SEFDM and also demonstrates the performance improvement of long-haul optical communication systems using SEFDM compared to the use of conventional OFDM, when fiber nonlinearities are considered. Different modulation formats ranging from4QAM to 32QAM are studied and it is shown that, for the same spectral efficiency and information rate, SEFDM signals allow a significant increase in the transmission distance compared to conventional OFDM signals
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