Miracle-dz/UniFAR-FTUs huggingface dataset:
The Strategies Used by Forced Migrants to Manage Bereavement as a Result of Multiple Losses

A forced migrant is a person who tries to settle in another country after leaving their own country unwillingly, but is psychologically plagued by the past and by everything that characterises their country of origin. Therefore, there is a twofold difficulty: the forced migrant has to integrate into a country that was not desired, which causes psychological stress, while feel weakened by the losses and traumas associated with their departure. The aim of this study was to determine what are the strategies employed by forced migrants to manage the grief experienced as a result of significant losses. The research took the form of a systematic review of the literature, following a search on the electronic platform EBSCO host for studies published between January 2006 and January 2016. The search results were subsequently evaluated, respecting the inclusion and exclusion criteria previously established. Seven studies met the inclusion criteria. The findings of these studies revealed that in order to manage the grief they experienced as a result of significant losses, many forced migrants used strategies based on work, socialisation, in religious observance, the continuation of their cultural practices and taking care of children. The results suggest the need to give space to forced migrants to express their suffering, helping them to seek strategies that facilitate them in managing the grief that stems from significant losses associated with their departure from their country of origin.
Peer Tutoring to Facilitate Cognitive Diffusion of English as a Foreign Language Learning: Using Speech Translation and Shadowing in Familiar Authentic Contexts

Learning and cognitive ability are necessarily connected. Learning occurs when people engage in a series of cognitive processes. In this study, we examined how English as a foreign language (EFL) learners’ cognitive abilities diffuse (i.e., change) effectively from a basic level (i.e., Remember, Understand) to a more advanced level (i.e., Apply) with the assistance of a peer-tutoring strategy that pairs high-achieving students with lower achieving students and asks them to use the mobile application, ezTranslate, in a familiar, authentic context. The results showed that the experimental students (i.e., the students who received peer tutoring) significantly outperformed the control students (i.e., the students who worked individually) on the posttest. Furthermore, throughout the learning activity, the majority of the experimental students’ cognitive abilities transitioned from a basic to a higher level. Given these results, we suggested that peer tutoring is particularly advantageous because it helps students engage in high-level cognitive learning. By including mobile technology support with peer tutoring, teachers can utilize their students’ differing abilities to promote collaborative learning, which results in not only successful learning but also encourages positive social interaction and results in high-level cognitive learning.
Hubble Space Telescope Space Telescope Imaging Spectrograph Imaging of the Host Galaxy of GRB 980425/SN 1998bw

We present Hubble Space Telescope Space Telescope Imaging Spectrograph observations of ESO 184-G82, the host galaxy of the gamma-ray burst GRB 980425 associated with the peculiar Type Ic supernova SN 1998bw. ESO 184-G82 is found to be an actively star-forming SBc subluminous galaxy. We detect an object consistent with being a point source within the astrometric uncertainty of 0. ″018 of the position of the supernova. The object is located inside a star-forming region. The object is ≳1 mag brighter than expected for the supernova based on a simple radioactive decay model. This implies either a significant flattening of the light curve or a contribution from an underlying star cluster.
Physical layer security in wireless networks: intelligent jamming and eavesdropping

This work aims at addressing two critical security issues residing in the physical layer of wireless networks, namely, intelligent jamming and eavesdropping. In the first two chapters we study the problem of jamming in a fixed-rate transmission system with fading, under the general assumption that the jammer has no knowledge about either the codebook used by the legitimate communication terminals, or the source’s output. Both transmitter and jammer are subject to power constraints which can be enforced over each codeword (peak) or over all codewords (average). All our jamming problems are formulated as zero-sum games, having the probability of outage as pay-off function and power control functions as strategies. We provide a comprehensive coverage of these problems, under fast and slow fading, peak and average power constraints, pure and mixed strategies, with and without channel state information (CSI) feedback. Contributions to the eavesdropping problem include a novel feedback scheme for transmitting secret messages between two legitimate parties, over an eavesdropped communication link, presented in Chapter 4. Relative to Wyner’s traditional encoding scheme, our feedback-based encoding often yields larger rate-equivocation regions and achievable secrecy rates. More importantly, by exploiting the channel randomness inherent in the feedback channels, our scheme achieves a strictly positive secrecy rate even when the eavesdropper’s channel is less noisy than the legitimate receiver’s channel. In Chapter 5, we study the problem of active eavesdropping in fast fading channels. The active eavesdropper is a more powerful adversary than the classical eavesdropper. It can choose between two functional modes: eavesdropping the transmission between the legitimate parties (Ex mode), and jamming it (Jx mode) – the active eavesdropper cannot function in full duplex mode. We consider two scenarios: the best-case scenario, when the transmitter knows the eavesdropper’s strategy in advance – and hence can adaptively choose an encoding strategy – and the worst-case scenario,
Action recognition using deep learning

In this thesis we study deep learning architectures for the problem of human action recognition in image sequences, i.e. the problem of automatically recognizing what people are doing in a given video. As unlabeled video data is easily accessible these days, we first explore models that can learn meaningful representations of sequences without actually having to know what is happening in the sequences at hand. More specifically, we first explore the convolutional restricted Boltzmann machine (RBM) and show how a stack of convolutional RBMs can be used to learn and extract features from sequences in an unsupervised way. Using the classical Fisher vector pipeline to encode the extracted features we apply them on the task of action classification. We move on to feature extraction using larger, deep convolutional neural networks and propose a novel architecture which expresses the processing steps of the classical Fisher vector pipeline as network layers. By contrast to other methods where these steps are performed consecutively and the corresponding parameters are learned in an unsupervised manner, defining them as a single neural network allows us to refine the whole model discriminatively in an end to end fashion. We show that our method achieves significant improvements in comparison to the classical Fisher vector extraction chain and results in a comparable performance to other convolutional networks, while largely reducing the number of required trainable parameters. Finally, we explore how the proposed architecture can be modified into a hybrid network that combines the benefits of both unsupervised and supervised training methods, resulting in a model that learns a semi-supervised Fisher vector descriptor of the input data. We evaluate the proposed model at image classification and action recognition problems and show how the model’s classification performance improves as the amount of unlabeled data increases during training.
Research on the visual/inertial integrated carrier landing guidance algorithm

In this article, we describe a visual/inertial integrated carrier landing guidance algorithm for aircraft carrier landing operations. The airborne vision system and the inertial navigation system are employed as sensors to obtain feature points of carrier runway as well as the aircraft inertial measurements. In this algorithm, visual and inertial information are integrated, and the Pose from Orthographic Projection and Scaling with Iterations algorithm is utilized to estimate aircraft position and carrier motion. A simulation was constructed validating this algorithm, and the results of this simulation show satisfactory accuracy as well as high efficiency in carrier landing guidance.
Preparation and filtration performance of the circular weft-knitted seamless weft-insertion fabric materials

Air particulate matter pollution has become a severe environment concern calling for filtration materials with great filtration performance. As the development of seamless forming technology, knitted filtration materials gradually show great potential. This study aimed to develop a novel kind of knitted seamless structure for filtration materials of filter bags with high production efficiency and excellent filtration performance. A new type of the circular weft-knitted seamless weft-insertion fabric (CKSW) filtration materials were developed on the modified circular knitting machine. This CKSW filtration materials consisting of the ground yarns, connection yarns and weft-insertion yarns, polyester full drawn yarns, and polyester draw texturing yarns with different yarn configurations were employed to realize series of CKSW samples. The polytetrafluoroethylene filaments with tourmaline particles were used to verify whether the static electric material produced an adsorption filtration effect on the CKSW filtration materials or not. After pretreatment, the filtration performance of the CKSW filtration materials was evaluated by analyzing its pore size, porosity, and filtration efficiency. Ultimately, the CKSW filtration materials with ground yarns and weft insertion yarns of draw texturing yarn and the connection yarns of full drawn yarn exhibited the most excellent filtration performance. The CKSW filtration materials show a high porosity of 87.14%, the pore size of 67.55 µm, and good filtration efficiency of 91.57% with the particles size of ≥ 5.0 µm. The successful fabrication of such knitted filtration materials may provide ideas for the development of filtration materials with new architecture mainly used as filter bags for baghouse.
Speech Acquisition in Monolingual Children Acquiring isiZulu in Rural KwaZulu-Natal, South Africa

In South Africa, isiZulu is the most widely spoken home language. However, research on children’s speech acquisition in isiZulu is minimal and there are no published speech assessments that speech-language therapists can use to identify children with speech sound disorders acquiring this language. In our research we aimed to document speech sound acquisition of 32 isiZulu-speaking children aged two years, six months to six years, five months in rural KwaZulu- Natal, South Africa. An isiZulu speech assessment was developed and used to assess the children’s speech in terms of phonetic acquisition, word shape and phonological processes. In the study, the implosive, plosives, nasals, affricates and vowels were mastered by the youngest children. The click /! ɡ/, approximant /l/ and fricative /ɦ/ may be among the last consonants to develop: they had not been mastered by the oldest group. Two-syllable structures were mastered early while structures of four/five syllables were still developing at 6;5. Participants in the older age groups could produce target words more accurately and used fewer phonological processes. The findings are discussed in relation to normative data from other Bantu languages. Knowledge of isiZulu speech sound development will assist clinicians working with isiZulu-speaking children in assessing and managing their speech difficulties: an important step towards ensuring that speech-language therapy services are relevant to all children in South Africa.
Comparison of multiple PM2.5 exposure products for estimating health benefits of emission controls over New York State, USA

Ambient exposure to fine particulate matter (PM2.5) is one of the top global health concerns. We estimate the PM2.5-related health benefits of emission reduction over New York State (NYS) from 2002 to 2012 using seven publicly available PM2.5 products that include information from ground-based observations, remote sensing and chemical transport models. While these PM2.5 products differ in spatial patterns, they show consistent decreases in PM2.5 by 28%–37% from 2002 to 2012. We evaluate these products using two sets of independent ground-based observations from the New York City Community Air Quality Survey (NYCCAS) Program for an urban area, and the Saint Regis Mohawk Tribe Air Quality Program for a remote area. Inclusion of satellite remote sensing improves the representativeness of surface PM2.5 in the remote area. Of the satellite-based products, only the statistical land use regression approach captures some of the spatial variability across New York City measured by NYCCAS. We estimate the PM2.5-related mortality burden by applying an integrated exposure-response function to the different PM2.5 products. The multi-product mean PM2.5-related mortality burden over NYS decreased by 5660 deaths (67%) from 8410 (95% confidence interval (CI): 4570–12 400) deaths in 2002 to 2750 (CI: 700–5790) deaths in 2012. We estimate a 28% uncertainty in the state-level PM2.5 mortality burden due to the choice of PM2.5 products, but such uncertainty is much smaller than the uncertainty (130%) associated with the exposure-response function.
Martial Arts in Postcolonial Times: Local Theories for Local Contexts

Article published in Ido Movement for Culture: Journal of Martial Arts Anthropology on 01 July 2019, available open access at: http://imcjournal.com/index.php/en/volume-xix-2019/contents-number-3/1489-martial-arts-in-postcolonial-times-local-theories-for-local-contexts.
Globalization and international accounting research: An agenda for the future

The study of international accounting is increasing in importance because of its ramifications upon business practices world-wide. International accounting is inextricably linked to the globalization movement that is sweeping all economies. Indeed, the availability of accounting information constitutes an integral and indispensable input to the existence and acceleration of this movement. This paper provides a step toward the examination of such beliefs and their impact on international accounting through a historical investigation of the academic literature in this field as exemplified by two journals: Advances in International Accounting and the International Journal of Accounting Education and Research. The wider project involved a hermeneutic interpretation of documents in an attempt to analyze trends in international accounting research appearing in academic accounting journals from 1987 to 1996 through the lens of postcolonialism. However, due to space constraints this paper focuses on the predominance and the championing of the globalization theme in this literature and its impact on research. This section of the paper provides a description of the methods employed in selecting the journals, the relevant time period, the articles constituting the data set, and the procedure followed in constructing the qualitative themes.
Toward an understanding of p-values: Simulation-based inference in a traditional statistics course

ABSTRACT The study presented in this article examined the impact of two simulation-based inference activities on students’ understanding of p-values in a second undergraduate statistics course. In the study, students familiar with traditional inference methods used physical and computer simulations to estimate p-values. To examine students’ conceptions before and after participation, students were prompted to write brief explanations of p-values, to apply these explanations in different contexts, and to self-evaluate their understanding. This article describes students’ varying conceptions of p-values and the ways in which students demonstrated improvement after engaging in simulation-based inference activities. Qualitative analysis of student responses suggests that students hold a range of conceptions of p-values even after a full semester of instruction; further, this study suggests that incorporating simulation-based inference into traditional courses has the potential to improve understanding of p-values and is a promising area for future research.
The Cell Switch-Off Approach for Energy Efficient Cellular Networks

Network densification is a key enabler for providing high data rates and ubiquitous coverage. Although it enables the ambitious target of 1,000-fold gains in capacity, installing more base stations (BSs) challenges the energy efficiency targets of future networks. Cell switch-off (CSO) approaches are proposed to reduce energy consumption in off-peak periods by switching off some BSs. In this thesis, we define an energy-efficient cellular network as one in which as few BSs as possible are switched on while still satisfying all the users demand and quality of service. This thesis contributes to the current state of knowledge by directing the CSO research towards a more realistic, feasible, and practical implementation. We do this by arguing for employing offline (static) CSO and for considering spatially irregular BS deployments. First, we propose a dynamic CSO algorithm based on the well-known set cover problem. Our algorithm outperforms a benchmark algorithm in terms of the total number of switched-off BSs. While dynamic CSO algorithms are designed to adapt to fast changes in demand distribution, proper interference modelling is very challenging. To overcome this challenge, we next study regular static CSO patterns and describe them systematically. We propose sector-based patterns, where not only entire BSs could be switched off (site-based), but their individual sectors too. We compare the performance of different CSO patterns in terms of their energy efficiency and the number of supported users. CSO patterns are advantageous for modelling interference properly, reducing coverage holes, and making the uplink transmissions more energy-efficient for users. Nevertheless, the underlying assumption is that the BSs are deployed according to a regular grid. Finally, we consider spatially irregular BS deployments as a more realistic network model; therefore, we study applying CSO to irregular network layouts with the objective of making the active BS locations as regular as possible. We test the suitability of several algorithms from the p-dispersion problem literature for networks with BSs deployed with variable amounts of regularity. We also demonstrate some of these algorithms on real BS locations.
Visualizing Language Change in a Corpus of Contemporary German

We introduce an approach to visualize language change in a large corpus of contemporary German newspapers, spanning the years 2000 to 2015, drawn from DeReKo (Kupietz et al. 2010). The visualization combines two factors involved in language change: Semantics and frequency change. Semantics of words is visualized by positioning them in two dimensions such that words with similar co-occurrence contexts are positioned closely together. This is accomplished in two steps: First, word embeddings are computed with the structured skip-gram approach described in (Ling et al. 2015), which takes into account word order. To calculate individual word embeddings for each year, we follow the approach of Dubossarsky et al. (2015) and Kim et al. (2014): The embeddings for the first year are initialized based on newspapers from 1950 to 1999 the embeddings for each subsequent year with the embeddings of the previous year. With this approach, the embeddings are comparable across years. Second, the 200 dimensions resulting from the first step are further reduced to two dimensions using t-Distributed Stochastic Neighbor Embedding (Van der Maaten & Hinton 2008). Frequency change is represented by color, ranging from violet for words with decreasing frequency to red for words with increasing frequency. To this end we calculate the slope of the generalized linear fit of a logistic transform on the relative frequencies in each year (Zuraw 2003) and map it to the color range. The goodness of fit for linear fits is 44.4% and for 2nd order fits 59.2%, thus, the colors characterize frequency change fairly well.
NFV and NFV‐based Security Services

In this chapter, we discuss 5G and security in the context of Network Functions Virtualization (NFV), a new transformative technology that combines the technology developments in distributed systems, software virtualization, and cloud computing to modernize telecommunication infrastructure and services. We will cover the content in three parts. The first part will discuss what NFV is and how NFV relates to 5G and security. In the second part, we survey the new security challenges that NFV brings and the new opportunities to solve security problems using NFV technologies. In the third part, we look at several exciting advancements in NFV‐based security solutions that can have a huge impact on the success of 5G and networking in general.
Developing a tool for learning concept maps

Modern day society requires students to memorise and understand a large number of facts. Currently, a powerful learning tool for comprehension is concept mapping, which refers to drawing meaningful relations between concepts in an associative network. For rote memorisation, flashcard systems are widely employed, which entails students going repeatedly through a set of questions and recalling their answers from memory. Critics have found concept mapping not entailing any method for retaining facts in memory, where others found flashcard learning extracting all meaning and context from the learning process. Therefore, a new learning tool is developed within this study, aiming to bridge the gap between aforementioned learning tools by integrating the visualisation of concept maps within the retrieval mechanism of flashcard learning. The new tool is an augmentation on the flashcard system, which asks the students to fill in empty concepts within given concept maps instead of to answer provided questions. Since retrieval practices — such as flashcard learning — have already been found to provide more meaningful learning than concept mapping in a recent study, the new tool is compared with a generic flashcard system for knowledge retention and comprehension. Furthermore, the usefulness and ease of use perceived by the participants are compared. Because of a low response rate, the results from the comparisons are only indicatory for further research. These results include the users of the new tools having a higher learning gain on knowledge retention questions than the flashcard users, and there being no significant difference in increased comprehension, perceived usefulness, and perceived ease of use of the systems.