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This study aims to test the self-determination theory (Ryan & Deci, 2000) that relates the type of gamification activities based on the student hybrid player type to the engagement of undergraduate students at a Saudi Arabia public university. By measuring the influence of the type of gamification and the hybrid player types on the student's engagement. And the interaction effects exist when the influence on the type of gamification depends on the hybrid player types' using an experimental 2X4 factorial design to answer the research questions: 1. What is the impact of tailored gamification activities on students' engagement? 2. What is the relationship between students' hybrid player types and their engagement? 3. What is the interaction between tailored gamification activities and students' hybrid player types? One hundred forty-one undergraduate students registered at an online course in a Saudi Arabia public university female section participated by using the gamified activities in Moodle learning management system for ten weeks. Data collected using Moodle logs and analyzed by 2X4 two-way between-subjects factorial MANOVA test with the hybrid player type (Philanthropist, Socializer, Free Spirit, Achiever) and gamification activities (traditional, tailored) as the factors and points, time, and clicks as dependent variables. The finding agreed with the literature on the positive effect of tailored gamification on undergraduate students' engagement. However, more investigation is needed to understand how students' player type affects their engagement, the Gamification Hexad user type interaction with the tailoring of game elements, and if there is other mediated variable that affects the customization process from beneficial to overwhelming. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Despite several recent advances, most of the electroencephalogram(EEG)-based brain-computer interface (BCI) applications are still limited to the laboratory due to their long calibration time. Due to considerable inter-subject/inter-session and intra-session variations, a time-consuming and fatiguing calibration phase is typically conducted at the beginning of each new session to acquire sufficient labelled training data to train the subject-specific BCI model. This thesis focuses on developing reliable machine learning algorithms and approaches that reduce BCI calibration time while keeping accuracy in an acceptable range. Calibration time could be reduced via transfer learning approaches where data from other sessions or subjects are mined and used to compensate for the lack of labelled data from the current user or session. In BCI, transfer learning can be applied on either raw EEG, feature or classification domains. In this thesis, firstly, a novel weighted transfer learning approach is proposed in the classification domain to improve the MI-based BCI performance when only few subject-specific trials are available for training. Transfer learning techniques should be applied in a different domain before the classification domain to improve the classification accuracy for subjects whom their subject-specific features for different classes are not separable. Thus, secondly, this thesis proposes a novel regularized common spatial patterns framework based on dynamic time warping and transfer learning (DTW-R-CSP) in raw EEG and feature domains. In previous transfer learning approaches, it is hypothesised that there are enough labelled trials available from the previous subjects or sessions. However, in the case when there are no labelled trials available from other subjects or sessions, domain adaptation transfer learning could potentially mitigate problems of having small training size by reducing variations between the testing and training trials. Thus, to deal with non-stationarity between training and testing trials, a novel ensemble adaptation framework with temporal alignment is proposed.

Governments have become more and more interested in embracing Information and Communication Technology (ICT), and have made a remarkable progress over the last few years. Electronic Government (e-government) - described as the strategic use of ICT to transform the public sector - is presently recognised as a driver and a key enabler of citizen-centric, cooperative, and seamless modern governance. E-government implementation implies not only a profound transformation in the way government interacts with the governed, but also a reinvention of its internal processes and how public organisations carry their business both internally as well as externally while interacting with the other segments of the community. Based on the literature, it is frequently claimed that the availability of an effective E-Government Readiness (EGR) assessment framework is a necessary condition for advancing e-government proper implementation. Most e-government appraisal models address the Electronic Service (e-service) dimension of e-government that focuses on the services provided by the government to the citizens on the Internet. This gives a very narrow perspective to e-government ignoring a key dimension: the Electronic Administration (e-administration), that highlights the importance of modernising the public sector, increasing government productivity, and transforming its internal processes. Furthermore, developed models assess E-Government Readiness (EGR) on a country as a whole without conducting an in-depth assessment on a public organisation scale. In addition, the majority of these models do not take into consideration the opinion of the civil servants involved in such e-government programs, a key stakeholder that affects their success. The objective of this thesis is to develop a framework that assesses EGR focusing on e-administration within public organisations through obtaining its employees‟ feedback. The suggested framework investigated the internal factors affecting EGR categorised into four dimensions: (i) strategy, (ii) people, (iii) technology, and (iv) processes. A number of measuring constructs are identified under each dimension. The framework components, relationships, and hypotheses were derived from the literature on Electronic Readiness (e-readiness), EGR, Information Systems (IS) and Electronic Commerce (e-commerce) success. In order to test the proposed framework, the thesis examined the relations and interactions of these components in an emerging e-government environment using four case studies of different characteristics to represent public organisations in Egypt. These organisations cover municipalities, investment, tax payment, and health sectors. Quantitative data collection method was through distributing a questionnaire to a sample of employees in each organisation. Data obtained from the questionnaire in each organisation was triangulated with data gathered from other sources of evidence: (i) interviews with top management, (ii) documentations, (iii) archival records, and (iv) observations. Findings of the empirical research were evaluated against the framework suggested in the beginning leading to a final framework that assesses EGR of public organisations. Findings revealed that framework's hypotheses were all confirmed. Concerning Egypt's EGR assessment, results proved that processes, technology, and people have a high effect on EGR, whereas strategy has a modest impact on it. This reflects that strategy is not given a high value in terms of e-government and that top management need to further promote e-government within public Egyptian organisations. Findings revealed also the modest impact of strategy on the two dimensions: technology and processes compared with its high effect on people. The research highlighted also the different measuring constructs that have the highest weights in each of the four dimensions. This helps in understanding e-government environment of public organisations in Egypt, showing the main components that affect EGR. The thesis though provides a rich insight into investigating e-administration within public organisations especially in a developing country such as Egypt, and presents a systematic approach to assess EGR of public organisations based on the four e-government building blocks: (i) strategy, (ii) people, (iii) technology, and (iv) processes. Therefore the thesis contributes to research areas in the literature related to assessments of information systems, e-commerce, e-readiness, and e-government readiness.

A brief introduction is given to benzodiazepine drugs and benzodiazepine receptors, particularly in human brain tissue. Human post-mortem brain tissue samples and their authentic blood samples were collected at the City Mortuary, Glasgow.

This study aims to test the self-determination theory (Ryan & Deci, 2000) that relates the type of gamification activities based on the student hybrid player type to the engagement of undergraduate students at a Saudi Arabia public university. By measuring the influence of the type of gamification and the hybrid player types on the student's engagement. And the interaction effects exist when the influence on the type of gamification depends on the hybrid player types—using an experimental 2X4 factorial design to answer the research questions: 1. What is the impact of tailored gamification activities on students’ engagement? 2. What is the relationship between students’ hybrid player types and their engagement? 3. What is the interaction between tailored gamification activities and students’ hybrid player types? One hundred forty-one undergraduate students registered at an online course in a Saudi Arabia public university female section participated by using the gamified activities in Moodle learning management system for ten weeks. Data collected using Moodle logs and analyzed by 2X4 two-way between-subjects factorial MANOVA test with the hybrid player type (Philanthropist, Socializer, Free Spirit, Achiever) andgamification activities (traditional, tailored) as the factors and points, time, and clicks as dependent variables.The finding agreed with the literature on the positive effect of tailored gamification on undergraduate students’ engagement. However, more investigation is needed to understand how students’ player type affects their engagement, the Gamification Hexad user type interaction with the tailoring of game elements, and if there is other mediated variable that affects the customization process from beneficial to overwhelming.

This dissertation examines whether the Western-driven model of recruitment to, and consequences of, high-risk activism that McAdam introduced before the internet applies to non-violent anti-regime campaigns in autocratic contexts after the social media revolution. I use the case of the 18-day non-violent Egyptian uprising of 2011 to investigate these topics. I specifically utilize data from the Arab Democracy Barometer survey and other micro- and macro-level sources. I find that face-to-face ties are most effective in recruitment to such movements. Online networks create new forms of dissent, such as online activism. Moreover, online ties are especially useful in mobilizing women. I also uncover that transitional periods that follow such campaigns increase political participation but might decrease support for democracy. My results stress the importance of social media to the recruitment process in autocratic gender-restrictive contexts and add to our understanding of the transitional periods.

How do we choose between different options based on their value? Conceptual frameworks of value-based choice describe the process in several stages, often (though not always) with the assumption that these stages are serial, discrete, and localized to different brain regions. Moreover, while several models of value-based decision-making exist at the cognitive level, models of the neural circuit underlying this process have mostly been limited to modeling value comparison. We sought to gain deeper insight into the neural mechanisms underlying value-based choice by examining the responses of neurons in the dorsal and subgenual anterior cingulate cortices (ACC) of rhesus macaques. Our findings in the dorsal anterior cingulate (dACC) are consistent with its direct involvement in the decision-making process. Moreover, neural responses to value in this region suggest an attentionally-aligned—rather than option-aligned—mechanism of choice; i.e. neurons respond to the value of the stimulus presented to the subject, rather than responding selectively to different options according to their identity. Our results also suggest that options are evaluated and preliminarily accepted or rejected as they are presented, rather than a comparison and choice process that only begins once evaluation of all options is complete. Finally, we find evidence that the attributes constituting the value of an option are not fully integrated into a unified value for that option. Many of these neural correlates were similarly found in the subgenual anterior cingulate cortex (sgACC); an adjacent prefrontal region whose role in decision-making is less understood. These findings recapitulate many of the insights gained from cognitive models of decision-making, suggesting that stages of the choice process proceed in parallel, utilize many of the same neural circuitry, and may be replicated across multiple brain regions. These results also illuminate the contours of a different implementation of value-based decision-making in neural circuits.

Stories are one of the main tools that humans use to make sense of the world around them. This ability is conjectured to be uniquely human, and concepts of agency and interaction have been found to develop during childhood. However, state-of-the-art artificial intelligence models still find it very challenging to represent or understand such information about the world. Over the past few years, there has been a lot of research into building systems that can understand the contents of images, videos, and text. Despite several advances made, computers still struggle to understand high-level discourse structures or how visuals and language are organized to tell a coherent story. Recently, several efforts have been made towards building story understanding benchmarks. As characters are the key component around which the story events unfold, character representations are crucial for deep story understanding such as their names, appearances, and relations to other characters. As a step towards endowing systems with a richer understanding of characters in a given narrative, this thesis develops new techniques that rely on the vision, audio and language channels to address three important challenges: i) speaker recognition and identification, ii) character representation and embedding, and iii) temporal modeling of character relations. We propose a multi-modal unsupervised model for speaker naming in movies, a novel way to represent movie character names in dialogues, and a multi-modal supervised character relation classification model. We also show that our approach improves systems ability to understand narratives, which is measured using several tasks such as their ability to answer questions about stories on several benchmarks.

INTRODUCTION: Previous studies have shown that osteocytes, the matrix-embedded cells in bone, control bone modeling and remodeling through direct contact with adjacent cells and via secreted factors that can reach cells in the bone marrow microenvironment (BMM). Osteocytes express several receptors including G protein-coupled receptors (GPCRs) and mice lacking the stimulatory subunit of G-proteins (Gsα) in osteocytes have abnormal myelopoiesis, skeletal abnormalities and reduced adipose tissue. This study aimed at evaluating the effects of osteocyte-secreted factors on myeloid cell proliferation and differentiation in vitro. To investigate cross-talk between osteocytes and the BMM, we established osteocytic cell lines lacking Gsα expression to study the molecular mechanisms by which osteocytes control myeloid cell proliferation and differentiation. METHODS: CRISPR/Cas9 was used to knockout Gsα in the osteocytic cell line Ocy454. Conditioned media (CM) from differentiated Ocy-GsαCtrl and Ocy-GsαKO cells were used to treat myeloid cells and bone marrow mononuclear cells (BMNCs) isolated from long bones of 6-8-week-old C57/BL6 mice. BMNCs were cultured with Macrophage Colony Stimulating Factor (M-CSF), Receptor Activator of Nuclear Factor Kappa β Ligand (RANKL) to induce osteoclast differentiation. Proliferation, TRAP staining, TRAP activity, resorption pit assay, F-actin ring formation and mRNA expression were used to evaluate cell proliferation, differentiation and function of the induced osteoclasts. Proteomics analysis of CM was performed to identify osteocyte-secreted factors capable of controlling myelopoiesis and osteoclastogenesis. RESULTS: Myeloid cells treated with CM from Ocy-GsαKO showed a significant increase in cell proliferation compared to Ocy-GsαCtrl CM and non-treated control. BMNCs treated with CM from Ocy-GsαCtrl and Ocy-GsαKO showed a significant increase in cell proliferation as compared to non-treated control. Osteoclast differentiation was significantly suppressed by CM from Ocy-GsαCtrl and further suppressed by CM from Ocy-GsαKO compared to non-treated control. Osteoclasts exposed to CM from Ocy-GsαKO showed a significant defect in activity and function as compared to cells exposed to CM from Ocy-GsαCtrl and non-treated cells. Osteoclast apoptosis was significantly enhanced by Ocy-GsαCtrl and Ocy-GsαKO CM compared to non-treated control. Among osteocyte secreted factors, we identified neuropilin-1 (NRP-1) as a Gsα-dependent osteocytic factor capable of suppressing osteoclastogenesis. CM from Ocy-GsαKO in which M-CSF was reduced by shRNA demonstrated decrease in BMNCs proliferation, demonstrating that osteocytes are also important sources of this cytokine. CONCLUSIONS: Osteocytes produce several Gsα-dependent and -independent secreted factors capable of supporting myelopoiesis, promoting macrophage proliferation and suppressing osteoclast formation. We identified osteocyte-derived NRP-1 as a novel factor capable of decreasing osteoclastogenesis. In addition, we found that M-CSF secreted by osteocytes is responsible in part for BMNC proliferation. Future studies should focus on determining the role of osteocyte-mediated NRP-1 and other secreted factor(s) in control of myelopoiesis and osteoclastogenesis.

Cyber-Physical Systems (CPS) entail the tight integration of and coordination between computational and physical resources. These systems are increasingly becoming vital to modernizing the national critical infrastructure systems ranging from healthcare, to transportation and energy, to homeland security and national defense. Advances in CPS technology are needed to help improve their current capabilities as well as their adaptability, autonomicity, efficiency, reliability, safety and usability.  Due to the proliferation of increasingly sophisticated cyber threats with exponentially destructive effects, CPS defense systems must systematically evolve their detection, understanding, attribution, and mitigation capabilities. Unfortunately most of the current CPS defense systems fall short to adequately provision defense services while maintaining operational continuity and stability of the targeted CPS applications in presence of advanced persistent attacks. Most of these defense systems use un-coordinated combinations of disparate tools to provision defense services for the cyber and physical components. Such isolation and lack of awareness of and cooperation between defense tools may lead to massive resource waste due to unnecessary redundancy, and potential conflicts that can be utilized by a resourceful attacker to penetrate the system.   Recent research argued against the suitability of the current security solutions to CPS environments. We assert the need for new defense platforms that effectively and efficiently manage dynamic defense missions and toolsets in real-time with the following goals: 1) Achieve asymmetric advantage to CPS defenders, prohibitively increasing the cost for attackers; 2) Ensure resilient operations in presence of persistent and evolving attacks and failures; and 3) Facilitate defense alliances, effectively and efficiently diffusing defense intelligence and operations transcending organizational boundaries. Our proposed solution comprehensively addresses the aforementioned goals offering an evolutionary CPS defense system. The presented CPS defense platform, termed CyPhyCARD (Cooperative Autonomous Resilient Defenses for Cyber-Physical systems) presents a unified defense platform to monitor, manage, and control the heterogeneous composition of CPS components. CyPhyCARD relies on three interrelated pillars to construct its defense platform. CyPhyCARD comprehensively integrates these pillars, therefore building a large scale, intrinsically resilient, self- and situation-aware, cooperative, and autonomous defense cloud-like platform that provisions adequate, prompt, and pervasive defense services for large-scale, heterogeneously-composed CPS. The CyPhyCARD pillars are: 1) Autonomous management platform (CyberX) for CyPhyCARD's foundation. CyberX enables application elasticity and autonomic adaptation to changes by runtime diversity employment, enhances the application resilience against attacks and failures by multimodal recovery mechanism, and enables unified application execution on heterogeneously composed platforms by a smart employment of a fine-grained environment-virtualization technology. 2) Diversity management system (ChameleonSoft) built on CyberX. ChameleonSoft encrypts software execution behavior by smart employment of runtime diversity across multiple dimensions to include time, space, and platform heterogeneity inducing a trace-resistant moving-target defense that works on securing CyPhyCARD platform against software attacks. 3) Evolutionary Sensory system (EvoSense) built on CyberX. EvoSense realizes pervasive, intrinsically-resilient, situation-aware sense and response system to seamlessly effect biological-immune-system like defense. EvoSense acts as a middle layer between the defense service provider(s) and the Target of Defense (ToD) creating a uniform defense interface that hides ToD's scale and heterogeneity concerns from defense-provisioning management. CyPhyCARD is evaluated both qualitatively and quantitatively. The efficacy of the presented approach is assessed qualitatively, through a complex synthetic CPS attack scenario. In addition to the presented scenario, we devised multiple prototype packages for the presented pillars to assess their applicability in real execution environment and applications. Further, the efficacy and the efficiency of the presented approach is comprehensively assessed quantitatively by a set of custom-made simulation packages simulating each CyPhyCARD pillar for performance and security evaluation.  The evaluation illustrated the success of CyPhyCARD and its constructing pillars to efficiently and effectively achieve its design objective with reasonable overhead.

Scope of Study: This research incorporates the personnel transition rates, inherent in all industrial situations, into the aggregate planning problem, and introduces the definition of the aggregate production and manpower planning problem. Two models are developed. The first is a linear programming model in which the Orrbeck model is used for the purpose of comparison and as a point of departure from which the new model is developed. The second is an extension of the first model from a single objective to a multiple objectives decision making model, and the goal programming is used as a method of multiple objectives procedures. The analysis of these models indicate their capabilities in presenting more realistic situations than existing models. A nondominance algorithm is developed to test the dominance of the goal programming solution, and to generate a nondominated solution if the goal programming solution turns out to be dominated. Also, a solution methodology for linear goal programming to include all the goals in the optimization process is proposed.