Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Emotions in Personalization: Detecting Emotions in Real-Time as Context Information

Emotion as contextual information is increasingly recognized to be essential variables to web personalization but is still an underresearched topic. Poor assumptions are made about user preferences as current personalization technology only gather historical data, without considering real-time information besides factors like time, location, and device. As a consequence, consumers have a bad user experience because the content is deemed to be irrelevant. The researcher introduces contextual personalization as a system-initiated process that considers the user’s current emotional state as contextual information to address the individual user with relevant content. This master’s thesis investigates how providers can offer a better user experience by utilizing emotions as part of contextual information in the personalization process. By employing a mixedmethod design, combining both qualitative and quantitative methods from user-centered design and affective computing, user needs and user behavior during specific emotional states were identified. The following investigation is twofold; the first part involves identifying emotional states with current emotion detection technology on the market, as well as empirically validate the effectiveness and reliability of the software. The second part of the project investigates whether the user’s emotional state affects the user experience and the user’s perception of content relevance. By using methods adapted mainly from previous studies, participants were induced with a specific emotion before interacting with a website. The results in the first experiment suggest that current face analysis technology can detect the intended emotion from even microexpressions. The results in the second experiment did not show significant differences between the two groups on perceived content relevance or the user experience. The data still yields indications that there is an emotional affect in interaction.
Blended Learning in English Language Teaching Contexts

The use of Blended Learning in English language teaching (ELT) contexts has increased significantly during the past decade . The present study reveals an overview of Blended Learning in ELT by considering where the term originated and by seeking to define what it means. This study also demonstrates an overview of Blended Learning through relevant literature and the current studies on Blended Learning in ELT contexts. Different blends and strategies used in implementing Blended Learning in ELT contexts are presented. Literature survey in recent study reveals that Blended Learning is more favorable than pure face-to-face or online instruction and offers advantages of Blended learning approach over them. Besides, the researcher demonstrates an overview of the limitations of the Blended Learning approach in ELT. Finally, the researcher concludes that Blended Learning might be an efficient instructing approach and recommends conducting further research on teachers’ required skills for using Blended Learning in ELT contexts.
The Performance Of Value Stocks And Growth Stocks: The Hong Kong Stock Market 1981-2005

Abstract This study finds that value stocks outperformed growth stocks in the case of the Hong Kong market over the period 1981 to 2005. It also finds that this is the case for the two sub-periods before and after the Asian financial crisis in 1997. Value stocks continued to outperform growth stocks after allowing for the firm size effect. The difference in return between value stocks and growth stocks increased when equally weighted portfolio returns were compared with value-weighted returns. The results were mixed when comparing risk adjusted returns using standard deviation as risk measure. The results of this study are in line with a number of international as well as South African studies.
Robust Engineering of Dynamic Structures in Complex Networks

OF THE DISSERTATION Robust Engineering of Dynamic Structures in Complex Networks by Walter Botongo Bomela Doctor of Philosophy in Electrical Engineering Washington University in St. Louis, August 2018 Research Advisor: Professor Jr-Shin Li Populations of nearly identical dynamical systems are ubiquitous in natural and engineered systems, in which each unit plays a crucial role in determining the functioning of the ensemble. Robust and optimal control of such large collections of dynamical units remains a grand challenge, especially, when these units interact and form a complex network. Motivated by compelling practical problems in power systems, neural engineering and quantum control, where individual units often have to work in tandem to achieve a desired dynamic behavior, e.g., maintaining synchronization of generators in a power grid or conveying information in a neuronal network; in this dissertation, we focus on developing novel analytical tools and optimal control policies for large-scale ensembles and networks. To this end, we first formulate and solve an optimal tracking control problem for bilinear systems. We developed an iterative algorithm that synthesizes the optimal control input by solving a sequence of state-dependent differential equations that characterize the optimal solution. This iterative scheme is then extended to treat isolated population or networked systems. We demonstrate the robustness and versatility of the iterative control algorithm through diverse applications from different fields, involving nuclear magnetic resonance (NMR) spectroscopy and x imaging (MRI), electrochemistry, neuroscience, and neural engineering. For example, we design synchronization controls for optimal manipulation of spatiotemporal spike patterns in neuron ensembles. Such a task plays an important role in neural systems. Furthermore, we show that the formation of such spatiotemporal patterns is restricted when the network of neurons is only partially controllable. In neural circuitry, for instance, loss of controllability could imply loss of neural functions. In addition, we employ the phase reduction theory to leverage the development of novel control paradigms for cyclic deferrable loads, e.g., air conditioners, that are used to support grid stability through demand response (DR) programs. More importantly, we introduce novel theoretical tools for evaluating DR capacity and bandwidth. We also study pinning control of complex networks, where we establish a control-theoretic approach to identifying the most influential nodes in both undirected and directed complex networks. Such pinning strategies have extensive practical implications, e.g., identifying the most influential spreaders in epidemic and social networks, and lead to the discovery of degenerate networks, where the most influential node relocates depending on the coupling strength. This phenomenon had not been discovered until our recent study.
College-Going Expectations and the Factors Predicting Whether Students Sign Up for Washington's College Bound Scholarship Program? A Mixed Methods Evaluation. CEDR Working Paper No. 07292019-1-1.

We investigate factors influencing student sign-ups for Washington State’s College Bound Scholarship (CBS) program and consider whether there is scope for the program to change college enrollment expectations. We find that student characteristics associated with signing the scholarship closely parallel characteristics of low-income students who attend 4-year colleges, suggesting that signing the pledge is driven largely by pre-existing expectations of college-going. We also find evidence that student sign-up rates are lower than has been previously reported, which is important given the perception among program administrators that nearly all eligible students sign up.
It's Not Me, it's You: Testing a Moderated Mediation Model of Subordinate Deviance and Abusive Supervision Through the Self‐Regulatory Perspective

Synthesizing self&#8208;regulatory theories, we provide new insights into the antecedents of abusive supervision. We, from the perspective of supervisor's self&#8208;regulatory resources depletion or impairment, introduce supervisor hindrance stress as an underlying mechanism of the subordinate deviance&#8211;abusive supervision relationship: this mediated relationship will be intensified at the level of high subordinate job performance. In addition, we develop a complex contingency model and propose a three&#8208;way interaction (i.e., subordinate deviance, job performance, supervisor outcome dependence) to obtain the complete understanding of the subordinate deviance&#8211;abusive supervision relationship facilitated through the supervisors&#8217; hindrance stress. To test our moderated moderated mediation model, we gathered time&#8208;lagged and multisource data from a large food service company located in southern China. We collected data at two different points (i.e., Time 1 and Time 2) from supervisors and their direct reports (N&#160;=&#160;298 responses from 68 supervisors and 298 direct reports), and findings provide support for the hypothesized moderated moderated mediation model of our study. We highlight the implications of our study for theory, research, and practice.
Difference between Expectations and Perceptions of Students Regarding Service Quality of Public Sector HEIs.

The aim of the present study is to find the gap between expectations and perceptions of students regarding the service quality of higher education public institutions of Lahore, Pakistan. Paired sample t-test was used to explore the gap between expectation and perception of the students of the higher education of the public institutions of Lahore. Stratified random sampling technique was used to collect the data from the students. The results indicated that there were differences between the expectations and perceptions of the students which relate to Reliability, Responsiveness and Assurance dimension. There was no significant difference between the expectations and perceptions of the students towards service quality of higher education public institutions of Lahore, Pakistan in terms of Assurance and Empathy. Research limitations: The data was only collected from the capital city of the province of Punjab. Moreover, the study focused only on higher education public institutions. The research methodology of this study is different from all the other studies which were conducted on this topic. In this study, we have focused to find the problem that students may face in service quality in higher education public institutions.
The Contextual Correlates of School Shootings

Abstract Research on school shootings remains limited, focusing primarily on individual-level risk factors, contagion, and prevention. The community effects literature on homicide and exposure to violence, however, suggests that contextual correlates also play an important role. This study examines whether macro-environmental characteristics impact the odds of a school district experiencing a shooting. A penalized maximum likelihood logistic regression model was used to compare 253 school districts in the United States that experienced at least one shooting from the 1998/1999 to 2017/2018 school years to the 13,201 that did not. Results indicate that districts with high enrollments and expenditures and greater levels of disadvantage and violent crime are at a higher risk for a school shooting. School shootings share similar macro-level contextual risk factors with other types of violent crime. Researchers should account for the context in which a school shooting occurs to avoid inflating the influence of individual-level risk factors.
Exploring the use of online social network activity and smartphone photography as an intervention to track and influence emotional well-being

The proliferation of internet and mobile technologies has expanded the means of detecting and influencing mental health, with this thesis focusing on the affective phenomena associated with emotional well-being including mood, affect and emotion. Traditional detection techniques including surveys and self-reports are grounded in the psychological literature; however, they introduce an inhibiting burden on the participants. The ability to passively detect psychological state using technologies including online behavioural tracking and mobile sensors is a prevalent focus of the current literature. Traditional positive psychology interventions commonly involve emotionally expressive writing tasks which can also be tedious for participants. Augmenting traditional intervention techniques with technologies such as smartphone applications can be one method to modernise interventions. The first research study in this thesis aimed to utilise online social network (OSN) activity to detect mood changes. The study involved collecting the participants’ behavioural activities such as likes, comments and tweets from their Facebook and Twitter profiles. Machine learning was used to create an algorithm to classify participants according to their online activity and their self-reported mood as ground truth. The findings indicated that participants can be grouped into those who displayed positive, negative or weak correlations with their online activity. Following the classification, the system used a sliding window of 7 days to track the participant’s mood changes for those in the positive and negative groups. The second research study introduced a positive psychology intervention in the form
Dimensions of desistance : a qualitative longitudinal analysis of different dimensions of the desistance process among long-term prisoners in the Netherlands

In the past decades a growing body of literature has been dedicated to explain desistance from offending behaviour, or to answer the question why some offenders quit crime and others do not. Currently, more psychological explanations infuse a prominent line of research emphasizing the importance of subjective, individual factors coming from within the offender, such as developing a new sense of self-identity. The aim of this study was to gain more insight into different dimensions of desistance, focusing on two aspects of identity: future expectations and conventional aspirations, and investigated how these related to (non-)criminal behaviour over time. Furthermore, this study examined how the parole experience interacted with the different dimensions of desistance. This qualitative, longitudinal study followed 28 male prisoners serving a long-term sentence in the Netherlands during their transition from prison to society. Findings illustrated the importance of individual factors such as believing in one’s own abilities in the context of pre-release expectations, the lack of conventional scripts and role models, and the contribution of parole supervision to the desistance process. Yet, it also revealed the pain of failure for men attempting to refrain from crime, mostly relating to structural support such as employment or housing issues.
It’s a Match? the Influence of Goal Matching in Couple Therapy

Abstract The degree which partners have aligned goals for therapy is an important, understudied psychotherapy predictor. Growth models were performed to examine group differences in alliance and outcome variables. Results revealed couples reported significantly lower commitment and sexual satisfaction in the mismatched group at the intercept but no significant trajectory differences. The matching group reported higher individual- and between-partner alliances initially but as sessions progressed, the mismatch group displayed significantly higher within-alliance ratings. This suggests couples with matched versus mismatched goals start therapy in different places and therapists may play an important role helping couples become more aligned as therapy progresses.
Methodological Guidance Paper: High-Quality Meta-Analysis in a Systematic Review

This methodological guidance article discusses the elements of a high-quality meta-analysis that is conducted within the context of a systematic review. Meta-analysis, a set of statistical techniques for synthesizing the results of multiple studies, is used when the guiding research question focuses on a quantitative summary of study results. In this guidance article, we discuss the systematic review methods that support high-quality meta-analyses and outline best practice meta-analysis methods for describing the distribution of effect sizes in a set of eligible studies. We also provide suggestions for transparently reporting the methods and results of meta-analyses to influence practice and policy. Given the increasing use of meta-analysis for important policy decisions, the methods and results of meta-analysis should be both transparent and reproducible.
Scholarly Practice and Inquiry: Dynamic Interactions in an Elementary Mathematics Methods Course.

This paper represents research that exists at the crossroad of scholarly practice and scholarly inquiry. We share the design, enactment and empirical examination of an elementary methods course activity, Exploring and Supporting Student Thinking (ESST) which engaged 18 prospective teachers in two sessions of one on one problem posing with 3 grade students. Results mirror outcomes from existing literature on student interviews and letter exchanges.
Honey Evaluation Using Electronic Tongues: An Overview

Honey-rich composition in biologically active compounds makes honey a food products highly appreciated due to the nutritional and healthy properties. Food-manufacturing is very prone to different types of adulterations and fraudulent labelling making it urgent to establish accurate, fast and cost-effective analytical techniques for honey assessment. In addition to the classical techniques (e.g., physicochemical analysis, microscopy, chromatography, immunoassay, DNA metabarcoding, spectroscopy), electrochemical based-sensor devices have arisen as reliable and green techniques for food analysis including honey evaluation, allowing in-situ and on-line assessment, being a user-friendly procedure not requiring high technical expertise. In this work, the use of electronic tongues, also known as taste sensor devices, for honey authenticity and assessment is reviewed. Also, the versatility of electronic tongues to qualitative (e.g., botanical and/or geographical origin assessment as well as detection of adulteration) and quantitative (e.g., assessment of adulterants levels, determination of flavonoids levels or antibiotics and insecticides residues, flavonoids) honey analysis is shown. The review is mainly focused on the research outputs reported during the last decade aiming to demonstrate the potentialities of potentiometric and voltammetric multi-sensor devices, pointing out their main advantages and present and future challenges for becoming a practical quality analytical tool at industrial and commercial levels.
Sign Voice Bi-Directional Communication System (SVBi) for Blind, Deaf/Dumb and Normal People

: Blind and deaf/dumb people face problems in communicating with others facing the difficulties in dealing with the communication technology. The goal of this paper is to design a communication system that is used to facilitate communication between blind, deaf/dumb and normal people using machine learning techniques. SVBiCommunication system helps blind person to hear voice through speaker, saying the word gestured by the deaf/dumb while the deaf will receive text that can be seen on LCD, representing the word said by the blind. SVBiCommunication works in two main directions, the first direction is processing the input from image to speech and also to text. The animated word gestures that are taken from the image are mapped with predefined language knowledge base into text. Then, the relevant audio is generated. The second direction is processing from speech to text. The voice from blind is converted into its corresponding text using ARM-Voice Recognition application.
Happiness, Gratitude, and Love

This chapter focuses on three of the core topics that are studied by positive psychologists: happiness, gratitude, and love. Each of these concepts has been the target of extensive research conducted by evolutionary psychologists. As such, we can now understand the ultimate factors that underlie these topics quite well. Happiness can be understood as an emotion that evolved largely to motivate people to move toward stimuli that facilitate survival or reproductive success. Gratitude evolved in connection with our strong tendencies toward reciprocal altruism, helping people keep positively connected to others in small social groups. And love evolved largely because human infants are quite helpless and thus benefit strongly from biparental care. The evolutionary analyses in this chapter are detailed and help shed light on the inner workings of each of these concepts.
A Context-Adaptive Ranking Model for Effective Information Retrieval System

When using Information Retrieval (IR) systems, users often present search queries made of ad-hoc keywords. It is then up to information retrieval systems (IRS) to obtain a precise representation of user’s information need, and the context of the information. Context-aware ranking techniques have been constantly used over the past years to improve user interaction in their search activities for improved relevance of retrieved documents. Though, there have been major advances in context-adaptive systems, there is still a lack of technique that models and implements context-adaptive application. The paper addresses this problem using DROPT technique. The DROPT technique ranks individual user information needs according to relevance weights. Our proposed predictive document ranking model is computed as measures of individual user search in their domain of knowledge. The context of a query determines retrieved information relevance. Thus, relevant context aspects should be incorporated in a way that supports the knowledge domain representing users’ interests. We demonstrate the ranking task using metric measures and ANOVA, and argue that it can help an IRS adapted to a user's interaction behaviour, using context to improve the IR effectiveness.
Sentiment Analysis of Twitter Data

The rapid expansion and acceptance of social media has opened doors into users opinions and perceptions that were never as accessible as they are with today’s prevalence of mobile technology. Harvested data, analyzed for opinions and sentiment can provide powerful insight into a population. This research utilizes Twitter data due to its widespread global use, in order to examine the sentiment associated with tweets. An approach utilizing Twitter #hashtags and Latent Dirichlet Allocation topic modeling were utilized to differentiate between tweet topics. A lexicographical dictionary was then utilized to classify sentiment. This method provides a framework for an analyst to ingest Twitter data, conduct an analysis and provide insight into the sentiment contained within the data.