Capacity Enhancement Strategy

This is an outdated document for CCAFS Phase I. The Phase II Capacity Development strategy can be found here: http://hdl.handle.net/10568/82591. Capacity enhancement is a central priority for CCAFS. There is strong institutional support for this prioritization in the mandate of the ESSP, which has an explicit strategy agenda to make sure that capacity enhancement is more than just a tool for implementation of scientific research, and CGIAR, for which collaboration and capacity enhancement are likely to have a high profile within the post-reform agenda

Teacher Educator Enhancement Strategy (TEES)

This teacher educator enhancement strategy (TEES) aims to create a comprehensive and holistic enhancement system that meets the needs of Ministry of Education personnel and teacher educators. This document lays out the preliminary enhancement design in order to solicit feedback and insights from Leadership and Teacher Development (LTD) program stakeholders. The strategy includes: 1) the enhancement program goal and objectives; 2) the principles and rationale that drive the enhancement program; 3) the necessary tools to be created; and 4) the detailed operational enhancement methodology and design

Low-cost sensors accuracy study and enhancement strategy

Today, low-cost sensors in various civil engineering sectors are gaining the attention of researchers due to their reduced production cost and their applicability to multiple nodes. Low-cost sensors also have the advantage of easily connecting to low-cost microcontrollers such as Arduino. A low-cost, reliable acquisition system based on Arduino technology can further reduce the price of data acquisition and monitoring, which can make long-term monitoring possible. This paper introduces a wireless Internet-based low-cost data acquisition system consisting of Raspberry Pi and several Arduinos as signal conditioners. This study investigates the beneficial impact of similar sensor combinations, aiming to improve the overall accuracy of several sensors with an unknown accuracy range. The paper then describes an experiment that gives valuable information about the standard deviation, distribution functions, and error level of various individual low-cost sensors under different environmental circumstances. Unfortunately, these data are usually missing and sometimes assumed in numerical studies targeting the development of structural system identification methods. A measuring device consisting of a total of 75 contactless ranging sensors connected to two microcontrollers (Arduinos) was designed to study the similar sensor combination theory and present the standard deviation and distribution functions. The 75 sensors include: 25 units of HC-SR04 (analog), 25 units of VL53L0X, and 25 units of VL53L1X (digital).The authors are indebted to the Spanish Ministry of Economy and Competitiveness for the funding provided through the research project BIA2017-86811-C2-1-R, directed by José Turmo, and BIA2017-86811-C2-2-R, directed by Jose Antonio Lozano-Galant. All these projects are funded with FEDER funds. Authors are also indebted to the Secretaria d’ Universitats i Recerca de la Generalitat de Catalunya, Catalunya, Spain for the funding provided through Agaur (2017 SGR 1482). It is also to be noted that funding for this research has been provided for Seyedmilad Komarizadehasl by the Spanish Agencia Estatal de Investigación del Ministerio de Ciencia Innovación y Universidades grant and the Fondo Social Europeo grant (PRE2018-083238).Peer ReviewedPostprint (published version

Preparing for generation Z:how can technology enhanced learning be firmly embedded in our students' learning experience? A case study from Abertay University

Abertay is a relatively small, modern university (undergraduate population of around 4000) with a wide portfolio and a diverse student population. Around 35% of our students are direct entry from local partner colleges to years 2 and 3 of our programmes and a significant number are first generation higher education within their families. As such, partnership working with colleges and support to aid student transitions are key aspects of Abertay’s provision. Since 2013/14, the university has developed and implemented a new Teaching and Learning Enhancement strategy that has catalysed wholescale transformation across the institution. This paper provides an overview of technology enhanced learning at the university with the drivers for change being to the quality of our students' learning experience, improve student retention and progression and enhance learners’ engagement

El impacto de la estrategia de mejora de recursos en el rendimiento de las pequeñas empresas

The objective of this study is to examine the impact of resource enhancement strategy in improving the performance of small business firms in Malaysia. A self-administered survey and simple random sampling technique were conducted by making 221 owners-managers of small business firms as a sample of the study. The data were analyzed using a two-stage approach to structural equation modeling (SEM). The results indicated that resource enhancement strategy has a positive and significant impact on improving small businesses' performance. The practical findings provide a much clearer conceptualization of how resource enhancement strategy overcomes the issue of competitiveness in a new venture and small business firms.El objetivo de este estudio es examinar el impacto de la estrategia de mejora de recursos en la mejora del desempeño de las pequeñas empresas en Malasia. Se realizó una encuesta auto administrada y una técnica de muestreo aleatorio simple al hacer 221 propietarios-gerentes de empresas pequeñas como muestra del estudio. Los datos se analizaron utilizando un enfoque de dos etapas del modelado de ecuaciones estructurales (SEM). Los resultados indicaron que la estrategia de mejora de recursos tiene un impacto positivo y significativo en la mejora del rendimiento de las pequeñas empresas. Los resultados prácticos proporcionan una conceptualización mucho más clara de cómo la estrategia de mejora de recursos supera el problema de la competitividad en una nueva empresa y pequeñas empresas

Speech Enhancement Strategy for Speech Recognition Microcontroller under Noisy Environments

Industrial automation with speech control functions is generally installed with a speech recognition sensor which is used as an interface for users to articulate speech commands. However, recognition errors are likely to be produced when background noise surrounds the command spoken into the speech recognition microcontrollers. In this paper, a speech enhancement strategy is proposed to develop noise suppression filters in order to improve the accuracy of speech recognition microcontrollers. It uses a universal estimator, namely a neural network, to enhance the recognition accuracy of microcontrollers by integrating better signals processed by various noise suppression filters, where a global optimization algorithm, namely an intelligent particle swarm optimization, is used to optimize the inbuilt parameters of the neural network in order to maximize accuracy of speech recognition microcontrollers working within noisy environments. The proposed approach overcomes the limitations of the existing noise suppression filters intended to improve recognition accuracy. The performance of the proposed approach was evaluated by a speech recognition microcontroller, which is used in electronic products with speech control functions. Results show that the accuracy of the speech recognition microcontroller can be improved using the proposed approach, when working under low signal to noise ratio conditions in the industrial environments of automobile engines and factory machines