Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Evaluation of Equal Gain Diversity Systems In Fading Channels

Next generation wireless systems are being designed to provide ubiquitous broadband link access to information infrastructure. Diversity techniques play a vital role in supporting such high speed connections over radio channels by mitigating the detrimental effects of multiuser interference and multipath fading. Equal gain combining (EGC) diversity receiver is of practical interest because of its reduced complexity relative to optimum maximal ratio combining scheme while achieving near-optimal performance. Despite this, the literature on EGC receiver performance is meager owing to difficulty in deriving the probability density function of the diversity combiner output. This problem is further compounded when the diversity paths are correlated. Since spatial, pattern, or polarization diversity implementations at a mobile handset are usually limited to a small diversity order with closely spaced antenna elements (owing to cost and ergonomic constraints), any performance analysis must be revamped to account for the effects of branch correlation between the combined signals. This thesis presents a powerful characteristic function method for evaluating the performance of a two-branch EGC receiver in Nakagami-m channels with nonindependent and non-identical fading statistics. The proposed framework facilitates efficient error probability analysis for a broad range of modulation/detection schemes in a unified manner. The thesis also examines the efficacy of an average diversity combiner in slotted direct sequence spread-spectrum access packet radio networks. A two-dimensional EGC diversity combining scheme is introduced, wherein a corrupted packet is retained and combined with its retransmission at the bit level to produce a more reliable packet. The mathematical analysis of the average diversity combiner presented in this thesis is sufficiently general to handle generalized fading channel models with independent fading statistics for a myriad of digital modulation schemes.
Patterns and Pedagogy: Exploring Student Blog Use in Higher Education.

As social and collaborative technologies emerge, educators and scholars continue to explore and experiment with how these tools might impact pedagogy. For over a decade, educators experimented with the use of blogs in academic settings, a tool that allows for students and instructors to enter into a rich dialogue. With most technology tools, users often leave ‘digital footprints’ throughout the environment. These footprints, in combination with other sources of data, allow researchers to explore relationships between the tool itself and the different types of end users. This study examines two years of institutional blog data, combined with demographic data to help describe the users of a blog platform. Different clusters of users are uncovered, and various use cases are explored, illustrating how different instructors choose to leverage blogs in the flow of a course. Using analysis of variance (ANOVA) to compare different blogging groups, results show a strong correlation between entry-dominant bloggers and growth in Grade Point Average (GPA) over time. With the rise in popularity of learning analytics, the results of this study might influence future learning analytics tools and systems
The Effect of Semantic Transfer on Iranian EFL Learners’ Lexical Representation and Processing

Psychological processes underlying the learning of vocabulary of additional language(s) (i.e. second or foreign language) is an under-researched area in spite of the advances that have improved our understanding of the nature of the vocabulary knowledge. The purpose of this study is to investigate the psychological processes underlying foreign language vocabulary learning in the light of the semantic transfer hypothesis. The participants were 20 EFL learners (9 males and 11females) in Iranian context. They were asked to perform a semantic judgment task in which they decided whether or not 2 English words were related in meaning. Two types of related word pairs served as critical stimuli: word pairs whose 2 members shared or did not share the same Persian translation. The procedure was carried out by a software program designed for the purpose of this research in order to measure the speed of the participant responses to these sets of words. The participants view toward their foreign language vocabulary learning and the interaction of their learning processes with the socio-cultural context they are exposed to was studied qualitatively using interview as the main data collection tool. The statistical analysis revealed that the Iranian EFL learners responded to the same-translation pairs significantly faster than to the different-translation pairs. The same-translation effect found in L2 speakers was taken as evidence for the presence of first language semantic structures in foreign language lexical representations and their continued involvement in the L2 processing. The qualitative findings also supported these findings. The pedagogical implications are also discussed.
Code clone detection technique of android layout codes using view attribute filtering

Each of Android application’s screens is composed by an XML file called “Android layout code files”. Developers can draw each screen by declaring user interface components in the Android layout code file. However, Android developers tend to use the same user interface components multiple times when declaring identical components in layout code, which leads to code clone issues that reduce the maintainability of code. There are many studies and techniques that detect code clones, but there is a lack of code clone research related to Android layout code. In this paper, we propose a new technique for detecting code clones in Android layout code. Our technique uses a tree-based model for data abstraction and compares each tree node by considering visual and non-visual View attributes of the Android layout codes. We selected 12 Android open source projects and developed a code clone detection tool to check validity of our approach. Our tool uses the proposed technique and two other existing techniques for comparison. The experimental results showed that our proposed technique exhibited higher precision and recall on the projects compared to the other two techniques. The results obtained from applying our technique to open source projects show that our technique is useful for detecting code clones. 572 Jaeyeon Lee, Jongwook Jeong and Hoh In
Feature extraction and image retrieval based on AlexNet

Convolutional Neural Network is a hot research topic in image recognition. The latest research shows that Deep CNN model is good at extracting features and representing images. This capacity is applied to image retrieval in this paper. We study on the significance of each layer and do image retrieval experiments on the fusion features. Caffe framework and AlexNet model were used to extract the feature information about images. Two public image datasets, Inria Holidays and Oxford Buildings, were used in our experiment to search for the influence of different datasets. The results showed the fusion feature of Deep CNN model can improve the result of image retrieval and should apply different weights for different datasets.
Human Action Localization And Recognition In Unconstrained Videos

As imaging systems become ubiquitous, the ability to recognize human actions is becoming increasingly important. Just as in the object detection and recognition literature, action recognition can be roughly divided into classification tasks, where the goal is to classify a video according to the action depicted in the video, and detection tasks, where the goal is to detect and localize a human performing a particular action. A growing literature is demonstrating the benefits of localizing discriminative sub-regions of images and videos when performing recognition tasks. In this thesis, we address the action detection and recognition problems.
The impact of library information literacy classes on first-year undergraduate students’ search behaviour

The aim of this study was to investigate whether or not the library courses in information literacy (IL) taught at Ostfold University College had an impact on the students’ search behaviour. To find out, 19 students were interviewed and observed about this topic. The results showed that there were only slight differences in search behaviour between those who had attended the IL sessions and those who had not. Many students used Google as their starting point for searching for information. In this paper, we discuss how these findings can be implemented when developing future library courses on information searching.
E-books: Are we on the same page?

ABSTRACT Libraries are making great efforts acquiring, maintaining, and promoting electronic book (e-book) collections; therefore, understanding what preference users have regarding e-books will help with current and future collection-development decisions. For librarians to provide e-book resources and services effectively, a thorough understanding of faculty, staff, and student e-book needs and preferences is needed. A campus-wide online survey was conducted to gather this much-needed data. As the Walter W. Stiern Library at California State University, Bakersfield, moves toward a broader integrated print and electronic acquisition model, it needs to ensure that its users' information needs are being met.
Using Mobile Technology to Engage Middle School Students in the Scientific Practice of Argumentation via Screencasting

vii LIST OF TABLES xv LIST OF FIGURES xvii LIST OF ABBREVIATIONS xviii CHAPTER 1: INTRODUCTION 1 Science Education and Technology 4 Theoretical Underpinnings for the Study 6 Statement of the Problem 7 Purpose of the Study 8 Limitations 8 Summary 9 CHAPTER 2: REVIEW OF THE LITERATURE 11 A Brief History of Inquiry 11 Defining Inquiry 13 The Role of Scaffolding 15 Assessing Inquiry 17 Argumentation 19 Scaffolding the Argumentation Process 22
Constructing and analyzing biological interaction networks for knowledge discovery

Many biological datasets can be effectively modeled as interaction networks where nodes represent biological entities of interest such as proteins, genes, or complexes and edges mimic associations among them. The study of these biological network structures can provide insight into many biological questions including the functional characterization of genes and gene products, the characterization of DNA-protein bindings, and the understanding of regulatory mechanisms. Therefore, the task of constructing biological interaction networks from raw data sets and exploiting information from these networks is critical, but is also fraught with challenges. First, the network structure is not always known in a priori; the structure should be inferred from raw and heterogeneous biological data sources. Second, biological networks are noisy (containing unreliable interactions) and incomplete (missing real interactions) which makes the task of extracting useful information difficult. Third, typically these networks have non-trivial topological properties (e.g., uneven degree distribution, small world) that limit the effectiveness of traditional knowledge discovery algorithms. Fourth, these networks are usually dynamic and investigation of their dynamics is essential to understand the underlying biological system. In this thesis, we address these issues by presenting a set of computational techniques that we developed to construct and analyze three specific types of biological interaction networks: protein-protein interaction networks, gene co-expression networks, and regulatory networks.
Enhancing Students’ Motivation in Learning English Grammar Through A Computer-Supported Learning Classroom Management

This research is to examine the students‘ motivational factors and attitude towards the learning of English grammar in a Computer supported Learning System. Twenty-nine students were taught with a student-centered approach and three grammar learning web sites were used frequently for classroom and individual English grammar practice, whereas another twenty-nine were taught with the traditional teachercentered approach. Both groups were given grammar correction and explanation tests before and after the study. After comparing the results of the pre-test and post-test with those of the control group, it was found that the experimental group excelled over the control group in both grammar correction and grammar explanation. It proved that students‘ implicit and explicit knowledge on English grammar was greatly improved by the computer-supported teaching methods and environment. Further interviews with the students also revealed that the new pedagogical practice had provided many positive motivational factors in supporting students‘ learning process.
Use and performance of the Forest Fire Weather Index to model the risk of wildfire occurrence in the Alpine region

Assessing a territory’s fire proneness is fundamental when planning and undertaking effective forest protection and land management. Accurate methods to estimate the risk of fire ignition in natural environments have been proposed over the last decades and digital mapping has been used to identify critical areas. The Canadian Forest Fire Weather Index is a well-known fire danger rating index created and improved during the last 45 years by the Canadian Forest Service. The goal of this paper is twofold. Firstly, we evaluated whether the Forest Fire Weather Index is an adequate instrument to predict fire ignition in Alpine and sub-Alpine areas using quite a large dataset of meteorological and forest fire data collected in the Lombardy region (Northern Italy) between 2003 and 2011. By means of a spatial binary regression model, we demonstrated that Forest Fire Weather Index has a significant impact on the probability of fire ignition. Since this approach allows us to account for other characteristics of the territory in order to provide a more accurate estimate of the spatial wildfire dynamics at a moderately large scale, the second goal of the paper aims at creating a model to assess fire risk occurrence using the Forest Fire Weather Index and land use information. It has been found that ignition can easily occur in large forested areas whereas denser urban areas are less exposed to fire since they usually have no fuels to ignite. Nevertheless, since human activity has a direct impact on fire ignition human presence, it fosters ignition in forested areas. Finally, the model, including these spatial dimensions, has been employed to derive a probability map of fire occurrences at 1.5 km resolution, which is a fundamental instrument to develop optimal prevention and risk management policy plans for the decision maker.
An exploratory study of reading procedural pictorial sequences

This paper presents the results of an exploratory study into the influence of picture content and verbal language reading directions on reading procedural pictorial sequences. A sequence of four pictures representing the procedure 'throw away after use' was tested in four graphic configurations (one-line horizontal, one-line vertical, two-line horizontal and rhomboid), which were designed to be read in specific directions. The same configurations were also presented with the pictures removed to explore the effect of content on reading sequences. The results confirmed that verbal language reading directions are generally used to follow pictorial sequences. However, when the graphic configurations used to represent sequences are unfamiliar and the starting point of the sequence is not clear in the configuration, pictorial content influences the reading direction.
Subjective wellbeing in New Zealand teachers: An examination of the role of psychological capital

Abstract Teaching is one of the most stressful occupations. This study explores how teachers’ psychological capital — a combination of hope, resilience, optimism and self-efficacy — is related to stress, wellbeing, appraisal and coping. Teachers (n = 1502) across New Zealand and from a range of teaching levels completed surveys. Participants with more psychological capital reported less stress and more wellbeing, saw work demands more as challenges than threats, and reported using more task-focused and less emotion-focused coping strategies. Psychological capital appeared to be directly related to increased wellbeing and reduced stress. Given the importance of teacher wellbeing for the profession and for students, we need ways to build teachers’ personal resources and, importantly, to ensure that teaching environments support wellbeing.
Producao e caracterizacao do carvao vegetal de especies e variedades de bambu

Simples of bamboo culms (B. vulgaris var. vittata, B. vulgaris, B. tuldoides, Dendrocalamus giganteus, Guadua angustifolia) were collected in 3 longitudinal positions from adult culms and carbonized in laboratory conditions. Eucalypt (E. urophylla hybrid) wood was used as a comparative parameter. Differences between the charcoal from the bamboo species and eucalypt were observed. The bamboo culms presented higher values of basic density, total extractives and smaller values of lignin and holocelulose in relation to wood samples. The bamboo culms provided higher charcoal yields and non-condensable gases. The bamboo charcoal was denser and with higher ash content in relation to wood charcoal. RESUMO Amostras de colmos de Bambusa vulgaris var. vittata, B. vulgaris, B. tuldoides, Dendrocalamus giganteus e Guadua angustifolia coletadas a várias alturas de colmos de touceiras adultas foram carbonizadas em condições de laboratório, caracterizando-se os carvões obtidos. Amostras de madeira de Eucalyptus foram utilizadas no processo de carbonização, para comparação dos resultados. Destacaram-se, dentre as diferenças observadas, a maior densidade básica, menor teor de lignina e holocelulose e maior teor de extrativos totais dos colmos. Estes apresentaram maiores rendimentos em carvão e em gases não condensáveis. Observou-se que o carvão do bambu é mais denso e tem maiores teores de cinzas em relação ao carvão da madeira.
The Relative Effectiveness of Text and Images in Image Search Result Listings

This study was conducted to determine the best type of image surrogate to use within search result sets: Text, Image Preview, or Text + Image Preview. Users performance and satisfaction with the three different image surrogates within search result sets were evaluated. Data was collected from 28 participants via a web-based system of questionnaires and logs of their interactions with result set presentations.
Subdimensional Expansion: A Framework for Computationally Tractable Multirobot Path Planning

Planning optimal paths for large numbers of robots is computationally expensive. In this thesis, we present a new framework for multirobot path planning called subdimensional expansion, which initially plans for each robot individually, and then coordinates motion among the robots as needed. More specifically subdimensional expansion initially creates a one-dimensional search space embedded in the joint configuration space of the multirobot system. When the search space is found to be blocked during planning by a robot-robot collision, the dimensionality of the search space is locally increased to ensure that an alternative path can be found. As a result, robots are only coordinated when necessary, which reduces the computational cost of finding a path. Subdimensional expansion is a exible framework that can be used with multiple planning algorithms. For discrete planning problems, subdimensional expansion can be combined with A* to produce the M* algorithm, a complete and optimal multirobot path planning problem. When the configuration space of individual robots is too large to be explored effectively with A*, subdimensional expansion can be combined with probabilistic planning algorithms to produce sRRT and sPRM. M* is then extended to solve variants of the multirobot path planning algorithm. We present the Constraint Manifold Subsearch (CMS) algorithm to solve problems where robots must dynamically form and dissolve teams with other robots to perform cooperative tasks. Uncertainty M* (UM*) is a variant of M* that handles systems with probabilistic dynamics. Finally, we apply M* to multirobot sequential composition. Results are validated with extensive simulations and experiments on multiple physical robots.
Effects of Digital Navigation Aids on Adults With Intellectual Disabilities

The purpose of this study was to compare the effects of three different navigation aids with students with intellectual disability. Participants included six college-aged students with intellectual disability who attended a postsecondary education program. An adapted alternating treatment design was used to compare a paper map, Google Maps on a mobile device, and an augmented reality navigation application. The results indicated that the augmented reality navigation application was functionally the most effective condition. Conclusions are discussed in the context of supporting people with intellectual disability by teaching navigation skills.
Automatic Recognition of Code-Switched Speech in Sepedi

Code switching (CS) is a natural phenomenon that is often observed in multilingual speakers. These speakers use words, phrases or sentences from foreign languages and embed them in sentences in the primary language. Automatic speech recognition (ASR) systems find code-switched speech difficult to process, and ASR performance is known to degrade in CS environments. We study the Sepedi/English CS phenomenon in the context of Sepedi ASR. Using experimentation, data collection and quantitative data analysis, we analyse techniques that can be used to effectively model code-switched speech in resource-scarce environments. The focus is on techniques that modify the pronunciation dictionary, in order to improve recognition accuracy. For this purpose, three new speech resources are designed, collected and curated: (1) the Radio Broadcast Corpus contains real examples of code-switching as observed during radio broadcasts; (2) the Sepedi Prompted Code-Switched (SPCS) Corpus is based on true code switching prompts, with each individual prompt recorded by multiple speakers in order to capture pronunciation variability occurring in code-switched speech; and (3) the National Center for Human Language Technology (NCHLT) Sepedi-English codeswitched subset (NSECSS) corpus does not contain naturally occurring code-switched speech, but rather English as spoken by Sepedi speakers. The latter corpus is particularly useful as its recording conditions and format match two related corpora: English produced by English speakers and Sepedi produced by Sepedi speakers. As part of corpus development, resource collection and analysis tools were developed and evaluated. Utilising these corpora, the implications of code-switched speech for ASR systems were evaluated. Various approaches to pronunciation modelling of code-switched speech were investigated and a novel method for pronunciation prediction developed. This new variant selection approach to modelling code-switched speech requires a two-step process: after grapheme-to-phoneme prediction of foreign words, phoneme-to-phoneme prediction (mapping the foreign phonemes to in-language phonemes) does not only take phoneme identity into account, but also graphemic context. A practical implementation of such an algorithm performed well during recognition experiments, both as a single approach and in combination with other existing approaches. The best overall results were obtained when multiple variants were generated per CS word, and variant-selection included in this process. Even though specifically applied to the Sepedi/English task, the methods themselves are language-independent.