Using Walking Interviews in Migration Research: A Systematic Review of the Qualitative Research Literature

In the field of migration research, the frequency of employing qualitative walking interviews has risen in recent years to delve into the construction, evolution, and negotiation mechanisms of migrant identities within everyday spatial practices. This novel mobile method emphasizes the interaction between micro-experience and macro-structure. It facilitates a shift away from viewing migrants as passive outsiders, empowering them with increased agency, and allow researchers to gain deeper insights into migrants’ emotional dynamics, life experiences, and self-identification within new social landscapes and power configurations. This systematic review aims to evaluate, integrate, and analyse the current empirical evidence in qualitative migration research using walking/go-along interviews for different types of migrants (defined as an individual who moves away from his or her place of usual residence, whether within a country or across an international border, temporarily or permanently, and for a variety of reasons). This review brings together for the first time the knowledge and insights from migration research that involves walking interviews. This review employs framework synthesis to analyse the 24 included articles, identifying five major themes: (1) synergising diverse research methods within different research designs; (2) adjustment of power dynamics; (3) migrants’ place-based threefold agency; (4) migrants' identity construction; (5) place-based sense of belonging or exclusion. By integrating these themes, the methodological contribution of this review lies in recognizing the advantages of combining walking interviews with other research methods, which lies in capturing the multidimensional aspects of mobility, allowing researchers to flexibly switch between methodological strategies and spatial scales. Additionally, this paper recommends a deeper exploration of migratory experiences to transcend prevailing practical knowledge and pay sensitive attention to potential ethical issues throughout the research. Such investigation has the potential to uncover the dynamic evolution of agency, identity construction, and the fluctuating sense of belonging among various migrants throughout their journey

Learning Rich Geographical Representations: Predicting Colorectal Cancer Survival in the State of Iowa

Neural networks are capable of learning rich, nonlinear feature representations shown to be beneficial in many predictive tasks. In this work, we use these models to explore the use of geographical features in predicting colorectal cancer survival curves for patients in the state of Iowa, spanning the years 1989 to 2012. Specifically, we compare model performance using a newly defined metric -- area between the curves (ABC) -- to assess (a) whether survival curves can be reasonably predicted for colorectal cancer patients in the state of Iowa, (b) whether geographical features improve predictive performance, and (c) whether a simple binary representation or richer, spectral clustering-based representation perform better. Our findings suggest that survival curves can be reasonably estimated on average, with predictive performance deviating at the five-year survival mark. We also find that geographical features improve predictive performance, and that the best performance is obtained using richer, spectral analysis-elicited features.Comment: 8 page

Towards α′\alpha'-finiteness: qq-deformed open string amplitude

Revisiting the Coon amplitude, a deformation of the Veneziano amplitude with a logarithmic generalization of linear Regge trajectories, we scrutinize its potential origins in a worldsheet theory by proposing a definition of its $q$-deformation through the integral representation of the $q$-beta function. By utilizing $q$-deformed commutation relations and vertex operators, we derive the Coon amplitude within the framework of the dual resonance model. We extend this to the open-string context by $q$-deforming the Lie algebra $\mathfrak{su}(1,1)$, resulting in a well-defined $q$-deformed open superstring amplitude. We further demonstrate that the $q$-prefactor in the Coon amplitude arises naturally from the property of the $q$-integral. Furthermore, we find that two different types of $q$-prefactors, corresponding to different representations of the same scattering amplitude, are essentially the same by leveraging the properties of $q$-numbers. Our findings indicate that the $q$-deformed string amplitude defines a continuous family of amplitudes, illustrating how string amplitudes with a finite $\alpha^\prime$ uniquely flow to the amplitudes of scalar scattering in field theory at energy scale $\Lambda$ as $q$ changes from $1$ to $0$. This happens without the requirement of an $\alpha^\prime$ expansion, presenting a fresh perspective on the connection between string and field theories

Sequential Keystroke Behavioral Biometrics for Mobile User Identification via Multi-view Deep Learning

With the rapid growth in smartphone usage, more organizations begin to focus on providing better services for mobile users. User identification can help these organizations to identify their customers and then cater services that have been customized for them. Currently, the use of cookies is the most common form to identify users. However, cookies are not easily transportable (e.g., when a user uses a different login account, cookies do not follow the user). This limitation motivates the need to use behavior biometric for user identification. In this paper, we propose DEEPSERVICE, a new technique that can identify mobile users based on user's keystroke information captured by a special keyboard or web browser. Our evaluation results indicate that DEEPSERVICE is highly accurate in identifying mobile users (over 93% accuracy). The technique is also efficient and only takes less than 1 ms to perform identification.Comment: 2017 Joint European Conference on Machine Learning and Knowledge Discovery in Database

CAP: A Context-Aware Neural Predictor for NAS

Neural predictors are effective in boosting the time-consuming performance evaluation stage in neural architecture search (NAS), owing to their direct estimation of unseen architectures. Despite the effectiveness, training a powerful neural predictor with fewer annotated architectures remains a huge challenge. In this paper, we propose a context-aware neural predictor (CAP) which only needs a few annotated architectures for training based on the contextual information from the architectures. Specifically, the input architectures are encoded into graphs and the predictor infers the contextual structure around the nodes inside each graph. Then, enhanced by the proposed context-aware self-supervised task, the pre-trained predictor can obtain expressive and generalizable representations of architectures. Therefore, only a few annotated architectures are sufficient for training. Experimental results in different search spaces demonstrate the superior performance of CAP compared with state-of-the-art neural predictors. In particular, CAP can rank architectures precisely at the budget of only 172 annotated architectures in NAS-Bench-101. Moreover, CAP can help find promising architectures in both NAS-Bench-101 and DARTS search spaces on the CIFAR-10 dataset, serving as a useful navigator for NAS to explore the search space efficiently.Comment: Accepted by IJCAI2

Hedgings em textos acadêmicos: uma perspectiva de aquisição de L3

This dissertation deals with the use of hedging strategies, which are considered a linguistic act to intensify or reduce the illocutionary force of scientific statements in academic writing, from the perspective of Third Language Acquisition (TLA). The study aims to analyze what the main factors are that influence these strategies in Chinese bachelor degree theses. Based on the hypothesis that multilinguals have a different pragmatic competence from bilinguals, which may influence the use of hedging strategies in academic writing, this study has been developed in three stages. In the first stage, the theoretical framework is discussed, focusing on TLA and hedging concepts and classifications in academic research articles. In the second stage, we present how the corpus was compiled and tagged, which consists of 60 texts in Chinese (L1), English (L2) and Portuguese (L3), written by Chinese bilingual and multilingual students with different English proficiencies. The third stage is to establish and analyze the associations of text moves, L2 status, speaker types and writing languages to the different hedging categories and effects, based on the data mining. The result shows that Chinese bilinguals apply hedging strategies with more frequency than multilinguals. Moreover, the texts written in English present more use of hedging with the effect of attenuation than in the other two languages. The study also shows that both text moves and second language proficiency may influence hedging strategies. However, each of them presents a different cross-linguistic influence for a given hedging category.Este trabalho trata do uso das estratégias de hedging, que são consideradas como uma ação de intensificar ou atenuar a força ilocucionária das afirmações científicas na produção acadêmica, sob uma perspectiva de Aquisição de Terceira Língua (AL3). O objetivo é analisar quais são os principais fatores que podem influenciar essas estratégias nos trabalhos de conclusão de curso de graduação, produzidos por alunos chineses. Partindo-se da hipótese de que os multilíngues possuem uma competência pragmática diferente dos bilíngues e que isso pode influenciar no uso das estratégias de hedging na produção científica, o estudo é realizado em três etapas. Na primeira etapa, são discutidas as principais teorias sobre a AL3 e os conceitos e classificações de hedging na produção acadêmica. Na segunda etapa, são realizadas a compilação e a anotação do nosso corpus de estudo, que é composto por 60 textos de mandarim (L1), inglês (L2) e português (L3), escritos por alunos chineses bilíngues e multilíngues, com diferentes proficiências em inglês. A terceira etapa visa estabelecer e discutir as principais associações dos fatores, quais são os movimentos textuais, proficiências em L2, tipos de falantes e línguas na escrita com as diferentes categorias e efeitos de hedging, a partir dos resultados fornecidos com base na mineração de dados. O resultado mostra que os chineses bilíngues possuem uma tendência a produzir mais hedging do que os multilíngues e que o inglês na escrita condiciona mais hedging de atenuação do que as outras duas línguas. Tanto os movimentos textuais, quanto as proficiências de L2 podem influenciar a produção de hedging, porém de maneira diferente para cada tipo de hedging

Why do the chinese learners produce the expression “de fato” in portuguese so frequently? = Por que os aprendizes chineses falam tanto a expressão “de fato” em português?

O presente artigo visa investigar por que os professores brasileiros têm a impressão de que os intercambistas chineses produzem, com uma alta frequência, a expressão “de fato” (“in fact” ou “actually” em inglês), que não é tão comumente usado pelos falantes brasileiros. O trabalho foi desenvolvido em quatro etapas: 1) análise de verbetes do termo “de fato” nos dicionários de português, português-inglês e português-chinês, e uma revisão dos estudos anteriores sobre essas palavras; 2) compilação de dois corpora em português, que consistem em textos acadêmicos escritos por alunos brasileiros e chineses; 3) classificação de “de fato” a partir do ponto de vista pragmático; 4) análise construtiva das estratégias pragmáticas do uso da expressão entre os dois corpora. O resultado mostra que embora os aprendizes chineses produzam, com mais frequência, a expressão “de fato” nos textos acadêmicos, a diferença das estratégias pragmáticas do uso nas comunicações contextuais talvez seja o fator principal que chamou a atenção dos falantes nativo