The Change of Language: A Critical Analysis of New Literacies on Twitter and in Educational Context

In modern society, there has been a trend that people tend to use effective tool in everyday correspondence. The development of social media network contributes to such situation. Therefore, a study is needed for the new literacies in the current communication of people’s daily life. With the aim to help educators better teach students in modern language context, the author adopted the information on Twitter, a widely-used social media network, and analysed it critically in educational context. It is found that the social media network brings both advantages and flaws to the English language. Such trend makes it more convenient for people to convey information but may confuse the readers and discourage them to read, especially aged people

An Analysis of ESOL Provision in the UK and Its Potential Future Development

ESOL provision plays an important role in immigrants’ settlement in the UK. Through previous research, it is found that ESOL provision is influenced by community, funding, immigration policy, learners’ needs for survival, and the current view of worldwide language. With the aim to study the correlation among these factors and the potential future of ESOL development in the UK, the author has reviewed relevant history and current concerns of ESOL provision and found that the need for ESOL provision is still increasing but that demand always exceeds provision and the inconsistency of funding results in learners’ lack of support. The major issues of ESOL provision are still the range of learners and consistency coherence of funding

Enumeration of General t-ary Trees and Universal Types

We consider t-ary trees characterized by their numbers of nodes and their total path length. When t=2 these are called binary trees, and in such trees a parent node may have up to t child nodes. We give asymptotic expansions for the total number of trees with nodes and path length p, when n and p are large. We consider several different ranges of n and p. For n→∞ and p=O(n^{3/2}) we recover the Airy distribution for the path length in trees with many nodes, and also obtain higher order asymptotic results. For p→∞ and an appropriate range of n we obtain a limiting Gaussian distribution for the number of nodes in trees with large path lengths. The mean and variance are expressed in terms of the maximal root of the Airy function. Singular perturbation methods, such as asymptotic matching and WKB type expansions, are used throughout, and they are combined with more standard methods of analytic combinatorics, such as generating functions, singularity analysis, saddle point method, etc. The results are applicable to problems in information theory, that involve data compression schemes which parse long sequence into shorter phrases. Numerical studies show the accuracy of the various asymptotic approximations. Key Words: Trees; Universal Types; Asymptotics; Path Length; Singular Perturbation

ChatGPT for Software Security: Exploring the Strengths and Limitations of ChatGPT in the Security Applications

ChatGPT, as a versatile large language model, has demonstrated remarkable potential in addressing inquiries across various domains. Its ability to analyze, comprehend, and synthesize information from both online sources and user inputs has garnered significant attention. Previous research has explored ChatGPT's competence in code generation and code reviews. In this paper, we delve into ChatGPT's capabilities in security-oriented program analysis, focusing on perspectives from both attackers and security analysts. We present a case study involving several security-oriented program analysis tasks while deliberately introducing challenges to assess ChatGPT's responses. Through an examination of the quality of answers provided by ChatGPT, we gain a clearer understanding of its strengths and limitations in the realm of security-oriented program analysis.Comment: 1 Table, 8 figure

Surface Engineering of Colloidal Quantum Dots for Advanced Photovoltaics

Solution-processable colloidal quantum dots (QDs) have attracted great interest for the applications in optoelectronics. Motivated by their band gap tunability, ease of property modification via surface engineering, phonon-bottleneck effect and efficient multiple exciton generation (MEG), a significant amount of research has been conducted particularly in the field of advanced photovoltaics (PV). Among the various types of QDs, lead selenide (PbSe) QDs are particularly attractive for applications in PV due to their relatively efficient MEG effect and potential advantage in carrier transport arising from their large exciton Bohr radius. The key factor inhibiting the development of efficient PbSe QD solar cells is surface defects arising from the air-sensitivity and non-sufficient passivation, which can form recombination centers and significantly limit the device performance. This thesis seeks to address these problems inherent to PbSe QDs, thin films and solar cells through different surface engineering approaches. The effect of using different surface halide ligands for PbSe QD thin film fabrication was investigated. It was discovered that the surface ligands can have dominant effect on both the air-stability and hot carrier lifetime of the PbSe QD thin films, indicating the significance of ligand selection for applications in hot carrier and MEG solar cells. Interfacial recombination at the QD and metal contact interfaces in a PbSe QD solar cell was found to be effectively suppressed by the introduction of a thin layer of cesium lead bromide perovskite nanocrystals. Evidences showed that the underlying mechanism for this could be either surface passivation of the QD layer or electron-blocking effect. This new device configuration had led to the report of the first PbSe QD solar cell with a power conversion efficiency (PCE) of over 7%. A new in-solution surface passivation method for PbSe QDs was developed using cesium lead halide perovskite nanocrystals as the passivating ligand source. The PbSe QDs obtained more robust hybrid halide surface passivation with this method. Consistent with the improvements in the photoluminescence quantum yield, the champion solar cell made with these PbSe QDs further improved the highest reported PCE to 8.2%, and also demonstrated superior air-stability lasting several months

Which Features are Learned by CodeBert: An Empirical Study of the BERT-based Source Code Representation Learning

The Bidirectional Encoder Representations from Transformers (BERT) were proposed in the natural language process (NLP) and shows promising results. Recently researchers applied the BERT to source-code representation learning and reported some good news on several downstream tasks. However, in this paper, we illustrated that current methods cannot effectively understand the logic of source codes. The representation of source code heavily relies on the programmer-defined variable and function names. We design and implement a set of experiments to demonstrate our conjecture and provide some insights for future works.Comment: 1 table, 2 figure

ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation

In addition to the unprecedented ability in imaginary creation, large text-to-image models are expected to take customized concepts in image generation. Existing works generally learn such concepts in an optimization-based manner, yet bringing excessive computation or memory burden. In this paper, we instead propose a learning-based encoder, which consists of a global and a local mapping networks for fast and accurate customized text-to-image generation. In specific, the global mapping network projects the hierarchical features of a given image into multiple new words in the textual word embedding space, i.e., one primary word for well-editable concept and other auxiliary words to exclude irrelevant disturbances (e.g., background). In the meantime, a local mapping network injects the encoded patch features into cross attention layers to provide omitted details, without sacrificing the editability of primary concepts. We compare our method with existing optimization-based approaches on a variety of user-defined concepts, and demonstrate that our method enables high-fidelity inversion and more robust editability with a significantly faster encoding process. Our code is publicly available at https://github.com/csyxwei/ELITE.Comment: Accepted by ICCV 2023, oral presentation. Code: https://github.com/csyxwei/ELIT