6 research outputs found

    The Teacher Professional Education Students' Perception on Learning Management System-based Online Learning

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    This research aimed to investigate the perceptions and impacts of online learning utilizing the SPACE (Electronic religious learning system application) among students enrolled in Teacher Professional Education (TPE) programs at State Islamic Religious Colleges. Employing a quantitative approach, the study utilized linear regression analysis and structural equation modeling through AMOS 23. Effectiveness was gauged using indicators proposed by Robert E. Slavin, encompassing quality of learning, appropriateness of learning level, intensity, and time. The study participants comprised students across three Teacher Professional Education Study Programs. The findings revealed that nearly all participants expressed ease in learning and perceived the modules within SPACE as more effective. They also indicated that the materials/modules in SPACE aligned well with the needs of TPE participants and found the learning procedures within SPACE easy to follow. Notably, incentive variables within implementation indicators had a direct influence on perceived ease of use (user convenience), subsequently impacting the perceived usefulness variable. For future research, integrating direct interview data from students and conducting comparative analyses between offline and online implementations in professional education would provide valuable insights

    Evaluating the prescribing and management practices of venlafaxine at a public sector psychiatric hospital

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    Neuropsychiatric conditions have been ranked third in South Africa according to some of the most recent reviews of disease burden, following human immunodeficiency virus/acquired immune deficiency syndrome and other infectious diseases (Bateman, 2012:70; South African Depression and Anxiety Group, 2018). For depressive disorders, the conventional selective serotonin reuptake inhibitors (e.g. fluoxetine), are common first-step treatments due to their relatively low toxicity and high tolerability (Rush et al., 2006:1231). The class of selective noradrenaline reuptake inhibitors (e.g. venlafaxine) is relatively new on the market. The first SNRI to be marketed in the United States was venlafaxine immediate-release (IR). It was approved by the United States FDA in 1993 (Sansone and Sansone, 2014:37) and was soon followed by the introduction of a micro-encapsulated extended-release (XR) formulation in 1997. Currently there is no published or readily available information concerning the prescribing and management patterns of venlafaxine as well as the incidence and types of adverse effects experienced by patients in the public health sector of South Africa besides the established increased in blood pressure

    Designing Robust Collaborative Services in Distributed Wireless Networks

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    Wireless Sensor Networks (WSNs) are a popular class of distributed collaborative networks finding suitability from medical to military applications. However, their vulnerability to capture, their "open" wireless interfaces, limited battery life, all result in potential vulnerabilities. WSN-based services inherit these vulnerabilities. We focus on tactical environments where sensor nodes play complex roles in data sensing, aggregation and decision making. Services in such environments demand a high level of reliability and robustness. The first problem we studied is robust target localization. Location information is important for surveillance, monitoring, secure routing, intrusion detection, on-demand services etc. Target localization means tracing the path of moving entities through some known surveillance area. In a tactical environment, an adversary can often capture nodes and supply incorrect surveillance data to the system. In this thesis we create a target localization protocol that is robust against large amounts of such falsified data. Location estimates are generated by a Bayesian maximum-likelihood estimator. In order to achieve improved results with respect to fraudulent data attacks, we introduce various protection mechanisms. Further, our novel approach of employing watchdog nodes improves our ability to detect anomalies reducing the impact of an adversarial attack and limiting the amount of falsified data that gets accepted into the system. By concealing and altering the location where data is aggregated, we restrict the adversary to making probabilistic "guess" attacks at best, and increase robustness further. By formulating the problem of robust node localization under adversarial settings and casting it as a multivariate optimization problem, we solve for the system design parameters that correspond to the optimal solution. Together this results in a highly robust protocol design. In order for any collaboration to succeed, collaborating entities must have the same relative sense of time. This ensures that any measurements, surveillance data, mission commands, etc will be processed in the same epoch they are intended to serve. In most cases, data disseminated in a WSN is transient in nature, and applies for a short period of time. New data routinely replaces old data. It is imperative that data be placed in its correct time context; therefore..

    Introduction

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