Miracle-dz/UniFAR-FTUs huggingface dataset:
Talking Physics: Two Case Studies on Short Answers and Self-explanation in Learning Physics

This thesis explores two case studies into the use of short answers and self-explanation to improve student learning in physics. The first set of experiments focuses on the role of short answer questions in the context of computer-based instruction. Through a series of six experiments, we compare and evaluate the performance of computer-assessed short answer questions versus multiple choice for training conceptual topics in physics, controlling for feedback between the two formats. In addition to finding overall similar improvements on subsequent student performance and retention, we identify unique differences in how students interact with the treatments in terms of time spent on feedback and performance on follow-up short answer assessment. In addition, we identify interactions between the level of interactivity of the training, question format, and student attitudinal views of the respective trainings. The second case study focuses on the use of worked examples in the context of multi-concept physics problems – which we call “synthesis problems. ” For this part of the thesis, four experiments were designed to evaluate the effectiveness of two instructional methods employing worked examples on student performance with synthesis problems; these instructional techniques, analogical comparison and self-explanation, have previously been studied primarily in the context of single-concept problems. As such, the work presented here represents a novel focus on extending these two techniques to this class of more complicated physics problem. Across the four experiments, both self-explanation and certain kinds of analogical comparison of worked examples significantly improved student performance on a target synthesis problem, with distinct improvements in recognition of the relevant concepts. More specifically, analogical comparison significantly improved student performance when the comparisons were invoked between worked synthesis exam-
How Transformational Leadership Fuels Employee’s Creative Performance Behaviors in the Workplace?

Supervisory transformational leadership behavior is attracting a widespread interest due to its fundamental quality that spurs subordinate confidence and optimism in the workplace. Although, despite the mounting evidence that links transformational leadership to different organizational and individual innovative outcomes, it is not yet been documented whether transformational leadership (TFL) can strengthen employee’s creative performance behavior in the workplace. Recently, Successful entrepreneurs thrive under competitive pressures in today’s high customer sensitivity to quality and innovative services. Hence, it's now clear that workplace creativity would be a potential solution for driving business success today. Although, the vital role of supervisory transformational leadership behavior in enhancing creative performance behavior of employees has not been dealt with in depth. However, the present paper aims to validate the potential and possible relationship between supervisory transformational leadership style and employee’s creative performance behavior in the workplace. To prove or disprove the assumptions underlined in this study, a cross-sectional research design, was conducted using data from 14 commercial banks operating in Rwanda (412 of total respondents). A variety of methods and tools were employed to examine the relationship between the variables hypothesized in this study. We conducted CFA in SEM-Amos, mean and standard deviation using SPSS and also Hayes macro process to measure the possible effect of each variable in this model. The overall results support our hypothesized model. In this regard, we believe that we have obtained comprehensive results proving and validating the usefulness of our hypothetical model.
The Rewards of Fiscal Consolidation: Sovereign Spreads and Confidence Effects

This paper investigates the effects of fiscal consolidation announcements on sovereign spreads in a panel of 21 emerging market economies during 2000-18. We construct a novel dataset using a global news database to identify the precise announcement date of fiscal consolidation actions. Our results show that sovereign spreads decline significantly following news that austerity measures have been approved by the legislature (congress or parliament), in periods of high sovereign spreads or in countries under an IMF program. In addition, consolidation announcements are less contractionary when sovereign spreads decline, with the reduction in output being half of the counterfactual case in which spreads do not respond to announcements. These results constitute direct evidence that confidence effects, in the form of lower sovereign spreads, are an important transmission channel of fiscal shocks. We also find that the role of confidence effects increases with the level of spreads such that countries with high spread levels stand to benefit the most from putting in place credible austerity packages.
The Constitutionality of the Prohibition of Hate Speech in terms of Section 10(1) of the Equality Act: A Reply to Botha and Govindjee

This is a reply to a critique by Botha and Govindjee (2017 PELJ 1-32) of our interpretation of the hate speech provisions of the Equality Act (Promotion of Equality and Prevention of Unfair Discrimination Act 4 of 2000) in Marais and Pretorius (2015 PELJ 901-942), in which we considered the constitutionality of section 10(1) of the Act, amongst other things. We address Botha and Govindjees' rejection of our view that hate speech is a form of unfair discrimination and that the most appropriate constitutional framework within which section 10(1) should be interpreted and assessed is sections 9 and 10 of the Constitution. We consider Botha and Govindjees' rejection of this point of departure, their opposing different interpretation of the role of the proviso in section 12 of the Act and, generally, their reasons for concluding that section 10(1) is unconstitutional. We maintain that Botha and Govindjee's proposals for reform unduly restrict the hate speech prohibition to cover exclusively expression that warrants criminalisation. In doing so, they fail to fully acknowledge the transformative obligation in terms of international law, the Constitution and the Equality Act, to prohibit and prevent unfair discrimination.
Statistical Methods for Structured Multilevel Functional Data: Estimation and Reliability

The thesis investigates a specific type of functional data with multilevel structures induced by complex experimental designs. Novel statistical methods based on principal component analysis that account for different layers of correlations in the data are introduced. A robust metric is proposed to evaluate the reproducibility of replicated functional and imaging studies. Shrinkage-based methods are extended to functional and imaging data with no or few replicates, and studies with low reliability. The proposed estimator is shown to correct for measurement error and improve prediction at the subject level by borrowing strength from the population average. Methods have been motivated by and applied to high-throughput physical activity measurements and several brain imaging studies based on different modalities including functional magnetic resonance imaging (fMRI), voxel-based morphometry, and diffusion tensor imaging (DTI). Fast algorithms are developed to expand the applicability of the methods proposed to ultra-high dimensional data. Readers: Brain Caffo (JHSPH Biostatistics) Peter Calabresi (Director, JHMI Division of Neuroimmunology) Ciprian Crainiceanu (advisor, JHSPH Biostatistics) Jennifer Schrack (JHSPH Epidemiology)
Spectrum sharing in the spatial domain.

The problem of spectrum sharing by exploiting the spatial domain is investigated in this thesis. The ultimate purpose of such a scheme is to mitigate the under-utilization of the scarce spectrum resource. By taking into account the availability of multiple antennas at the communicating nodes, an additional level of freedom can be exploited. Multiple-input multiple-output antenna systems have previously been shown to hold great promise: a linear growth in capacity without bandwidth expansion, enhanced transmission reliability using for instance space-time codes, and effective interference handling. The question of how these properties can be harnessed is explored by considering two perspectives: no cooperation and cooperation between users. For the cooperative scenario, a spatial-domain interweave spectrum sharing scheme is introduced that enables opportunistic transmission at a controlled cost to the license holders. The proposed scheme demonstrates three excellent characteristics: that exploitation of the spatial domain allows opportunistic communication in a “spatial hole,” that spectrum sharing is effectively enabled by inter-tier cooperation, and finally that in this scenario spatial-domain interweave is feasible with a “small” (as compared to the number of receive antennas at the incumbent) number of transmit antennas. In essence, this opens the possibility of the incumbents’ performance to be traded against opportunistic transmission. In the non-cooperative scenario, a spectrum sharing model between a small and large MU-MIMO system is proposed and analysed. The significant service antenna number asymmetry poses unique challenges and opportunities. In the limit of an infinite number of service antennas at one of the access point, the interference and noise power tends to zero and the transmit power can also be scaled back accordingly. These traits seem ideal for use in a spectrum sharing scenario, but in the present case with the coexistence of a conventional MIMO system and with a finite number of service antennas, how will the system behave? The resulting interference scenario is analysed explicitly both in the uplink and downlink, assuming linear receive and transmit equalizers, respectively. Characterization of the mean SINR operating point and required transmit power are presented, and concise transmit power scaling laws are derived. The scaling laws offer insight into how the system behaves with the number of service antennas and system load.
Does Financial Development and Inflation Spur Economic Growth in Thailand

The paper empirically examines the short- and long-run dynamics between financial development, inflation and economic growth during the post-1997 financial crisis in Thailand using battery of time series techniques. Based on the ARDL [2, 2, 0, 0], the study documents a long-run equilibrium between finance depth, inflation and growth. Granger causality tests based on the VECM further reveals that there is a bidirectional causality between finance-growth in Thailand, the finding accords with “the feedback hypothesis” or “bidirectional causality view”. Based on the VDCs and IRFs, the study discovers that the variations in the economic growth rely very much on its own innovations. To promote growth in the country, priority should be given for long run policies, i.e., the enhancement of existing financial institutions both in the banking sector and stock market and the preservation of low rate of inflation.
Stochastic neural computation without noise

Neural-network models of high-level brain functions such as memory recall and reasoning often rely on the presence of stochasticity. The majority of these models assumes that each neuron in the functional network is equipped with its own private source of randomness, often in the form of uncorrelated external noise. However, both in vivo and in silico, the number of noise sources is limited due to space and bandwidth constraints. Hence, neurons in large networks usually need to share noise sources. Here, we show that the resulting shared-noise correlations can significantly impair the performance of stochastic network models. We demonstrate that this problem can be overcome by using deterministic recurrent neural networks as sources of uncorrelated noise, exploiting the decorrelating effect of inhibitory feedback. Consequently, even a single recurrent network of a few hundred neurons can serve as a natural noise source for large ensembles of functional networks, each comprising thousands of units. We successfully apply the proposed framework to a diverse set of binary-unit networks with different dimensionalities and entropies, as well as to a network reproducing handwritten digits with distinct predefined frequencies. Finally, we show that the same design transfers to functional networks of spiking neurons.
Improved Photovoltaic MATLAB Modeling Accuracy by Adding Wind Speed Effect

Photovoltaic (PV) are generally modeled using mathematical equations that describe the PV system behavior. Most of the modeling approach is very simple in terms of that PV module temperature is calculated from nominal constant cell temperature such as ambient temperature and incoming solar irradiance. In this paper, we newly present MATLAB model particularly embedding the effect of wind speed to describe more accurate cell temperature. For analyses and validate purpose of the proposed model, solar power is obtained and compared with and without wind speed from the 50Wp PV module provided by vendor datasheet. In the simulation result, we found that power output of the module is increased to 0.37% in terms of cell temperature a degreed down when we consider the wind speed in the model. This result is well corresponded with the well-known fact that normal PV is 0.4% power changed by cell temperature a degree difference. Therefore it shows that our modeling method with wind speed is more appropriate than the methods without the wind speed effect.
Electrical Characterization Of PEDOT:PSS Based Flexible Organic Optoelectronic Devices

Electrical behavior of PEDOT:PSS films was investigated for potential application as anode in ITO-free flexible organic optoelectronic devices. Current-voltage, capacitance-voltage, capacitance-frequency and contact resistance-bending cycles characteristics were measured at different electrode configurations, as well as with and without post-deposition treatment procedure of the polymer film. Information about the hole mobility, conduction mechanism and electrical parameters’ stability at defined operational voltage and mechanical loading was extracted. It was found that UV treatment of the polymeric films is favorable for the improvement of its mechanical stability and the contact resistance, but it results in increasing of the interface capacitance. Optimum electrode gap of 6 mm was established, based on the results obtained for the hole mobility and the specific zones of current saturation from the currentvoltage characteristics. Operational voltage of the unipolar type structure PEDOT:PSS/copper was measured to be 3 V.
It's All About the Games! 2010 Vancouver Olympic and Paralympic Winter Games Volunteers

Despite volunteers being essential for the success of many mega sport events, there is little known about what motivates them to volunteer at such events. This study aims to address this gap. This article commences by developing Getz’s event portfolio into a new expanded sport event typology. It continues by presenting the results to three key questions: (1) who is volunteering? (2) what are their motivations for volunteering, and (3) what variables are most likely to be related to their intention to volunteer after the event. The study used an adaptation of the Special Event Volunteer Motivation Scale on volunteers at the 2010 Vancouver Olympic and Paralympic winter games. A principal components analysis of the 36 motivation items identified six factors that accounted for 58.3% of the variance, with the main factor entitled “All about the games. ” A regression analysis conducted to identify those variables most likely to indicate an intention to volunteer more after the games demonstrated that those who could see an advantage in more volunteering pregames were most likely to intend to increase their level of volunteering postgames. People with previous volunteering experience in events, sport, or community groups were less likely to indicate they would volunteer more after the event. The results and recommendations have implications for mega-multisport event organizing committees not just in respect of event delivery but in terms of a post-event volunteer legacy.
The use of routine case record data to evaluate quality of inpatient hospital care for newborns and children in Kenya

Quality of care assessment is one of the ways of evaluating what the health system is providing and can allow monitoring and evaluation exercises to track progress and identify gaps. Such monitoring however depends on an ability to measure quality with the availability of high quality data being central to these assessments. In low-resource settings routine health or hospital information system data are very limited, often of poor quality, and are typically summarized (e.g. total cases per ward) before being entered into the national health information system database. Such routine data very rarely include any information on a patient’s clinical findings or treatment. Thus at present routine data that are collected do not provide for individual patient level analyses of the process of care. The work presented in this PhD thesis seeks to demonstrate how case record data may be used to evaluate quality of care in routine hospital settings in Kenya and by doing this promote the availability of quality data and its effective use as one means to promote improvement in services provided in Kenyan hospitals. This work provides important insights into whether hospitalized children and newborns are receiving the correct care are using process of care assessments conducted in relatively large numbers of cases, across multiple locations and across time. I also explore how variable both the processes and outcomes of care may be across settings and examine the associations of this variability using more advanced statistical methods including hierarchical modelling.
Teaching the Arithmetic Sequence through Guided Discovery Learning: A Pedagogical Experiment in Viet Nam

“Let the student learn by discovery” has become the slogan of our country for recent years. Learning by discovery that has used by Vietnamese teacher is a term has appeared in Viet Nam in the past few years. This study proposes Guided Discovery learning to teach arithmetic sequence topic in Viet Nam high school. It is hypothesized that student. Student’s outcomes of teaching arithmetic sequence topic with Guided Discovery Learning are not greater than the ones of teaching this subject with the traditional method of instruction and students’ achievements after experiment are not better than students’ achievements before the experiment. Two eleven -classes were involved in the trial to investigate the effectiveness of Guided Discovery Learning,. The result suggests that students have better concept retention.
Non-Oil Exports and Economic Growth in Selected African Countries

This study investigates the relationship between non-oil exports and economic growth in selected African countries which include Algeria, Angola, Cameroun, Chad, Egypt, Equatorial Guinea, Ghana, Libya, Republic of Congo, Nigeria and Sudan from 1986-2018. The study has employed the Dynamic Panel Data Models and findings revealed that non-oil exports have positive relationship with economic growth in all the countries except Gabon in the long-run. The estimated coefficients are however not statistically significant at 5% level of significance. The study also found that there is positive impact of non-oil exports on economic growth in Angola, Egypt, Equatorial Guinea, Gabon, Libya, Nigeria, Republic of Congo and Sudan in the short-run while there is negative influence in Algeria, Cameroun, Chad and Ghana in the short-run. It is concluded from the findings of the study that non-oil exports have positive influence on economic growth in most selected African countries, although not significant. The study therefore, recommends that the African oil producing countries and oil producing countries generally should improve their production and exports of non-oil products relatively more than imports of these products. The products should also have international standard that could stand competitive at the world market. This would help to increase foreign earnings that could contribute positively to economic growth in one way, absorb the oil price shocks and create domestic jobs for the economy in another way.
EXPLORING CHALLENGES IN WRITING EFL MASTER THESES:
 STUDENTS AND SUPERVISORS' PERSPECTIVES

This study is intended to explore challenges in writing master theses from postgraduate English as Foreign Language (EFL) students' and supervisors' perspectives. To do so, 40 EFL postgraduate students and 10 supervisors were selected non-randomly based on availability sampling from five major Iranian universities. Qualitative data were gathered via semi-structured interviews the results of which were analyzed by utilizing thematic analysis. The findings revealed a number of main challenges faced by postgraduate students in writing master theses as reported by supervisors and the students themselves, some of which were common challenges for both groups. The main common challenge reported by both the students and supervisors was the students' lack of research knowledge including the inability to write academically using academic vocabularies, lack of research design knowledge such as analyzing data by SPSS software and choosing a researchable topic. Implications of the study for universities, EFL postgraduate students, and their supervisors are discussed in this study.
Speech Emotion Classification Analysis using Short-term Features

Speech is an auditory signal produced from the human speech production system used to express ourselves. In this era, speech signals are also used in biometric identification technologies and interacting with machines, so that it can give different response. Emotion recognition is not a new topic and researches and applications exist using different methods to extract specific features from the speech signals. This paper presents a classification analysis of emotional human speech only with short term processing features of the speech signals using artificial neural network based approach. Speech rate, pitch and energy are the most basic features of speech signal but they still have significant differences between emotions such as angry and sad. The most common way to analyze the speech emotion is to extract important features which are related to different emotion states from the voice signal. In the speech pre-processing phase, the samples of four basic types of emotional speeches sad, angry, happy, and neutral are used. Then feed those extracted short term features into the input end of the classifier and obtained different emotions at the output end. 23 short term audio signal features of 40 samples of two frames are selected and extracted from the speech signals to analyze the human emotions. These derived data along with their related emotion target matrix are fed to test and design the classifier using artificial neural network pattern recognition algorithm. The confusion matrix is generated to analyze the performance results. The overall correctly classified results for two times trained network is 73.8 %, while increasing the training times to ten, 95 % of the emotions are correctly classified. The accuracy of the neural network system is improved by multiple times of training. The overall system provides a reliable performance and correctly classifies more than 85 % for the new non-trained dataset.