845 resultados para Organization, vision, strategy, learning, monitoring


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Business and IT alignment is increasingly acknowledged as a key for organisational performance. However, alignment research lack to mechanisms that enable for on-going process with multi-level effects. Multi-level learning allows on-going effectiveness through development of the organisation and improved quality of business and IT strategies. In particular, exploration and exploitation enable effective process of alignment across dynamic multi-level of learning. Hence, this paper proposes a conceptual framework that links multi-level learning and business-IT strategy through the concept of exploration and exploitation, which considers short-term and long-term alignment together to address the challenges of strategic alignment faced in sustaining organisational performance.

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This paper considers the attitudes of students in Years 11, 12 and 13 towards French and, in particular, how they view the reasons behind their level of achievement. It reports findings from a small-scale pilot study, conducted in four schools and colleges, involving 83 students in Year 11, 26 in Year 12 and 14 in Year 13. The findings indicate that French is perceived by many Year 11 students to be difficult and uninteresting. These students, furthermore, do not consider that French is of much benefit in terms of their future career. The data suggest that there is a tendency among students in all three year groups to attribute their lack of success in French to their own low ability and to the difficulty of tasks set, which, it is argued, may affect their levels of motivation in a negative way. Few students in the study have any insight into the importance of learning strategies in overcoming difficulties experienced in language learning. Students' attitudes are then discussed in relation to learning strategy training. It is argued that if learners are encouraged to explore the possibility that their achievement in French may be related to the efficacy of the learning strategies they use, rather than to factors such as low ability or task difficulty, their self-concept, motivation and language learning achievements can be enhanced. A brief outline is given of a planned research project which proposes to address these issues further.

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Numerous studies have attempted to develop strategic alignment mechanisms. The strategic alignment mechanism is broken down into two categories namely: strategy process and strategy content. Our review shows that alignment research has been carried out in isolation. We see this as having had the effect of limiting the extent to which executives can understand elements of performance. We confer with a number of researchers in postulating that using a mechanism such as multilevel learning to combine strategy content and strategy process under one metaphor can greatly facilitate, through exploration and exploitation, the understanding not only of human interactions within a firm, but also of the interaction existent between a firm and its environment. The findings in this study further support the idea of integrating strategy process and content to have a better understating of alignment maturity and impact on business performance. It also elaborates the affect of misalignment in companies on performance.

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This document outlines a practical strategy for achieving an observationally based quantification of direct climate forcing by anthropogenic aerosols. The strategy involves a four-step program for shifting the current assumption-laden estimates to an increasingly empirical basis using satellite observations coordinated with suborbital remote and in situ measurements and with chemical transport models. Conceptually, the problem is framed as a need for complete global mapping of four parameters: clear-sky aerosol optical depth δ, radiative efficiency per unit optical depth E, fine-mode fraction of optical depth ff, and the anthropogenic fraction of the fine mode faf. The first three parameters can be retrieved from satellites, but correlative, suborbital measurements are required for quantifying the aerosol properties that control E, for validating the retrieval of ff, and for partitioning fine-mode δ between natural and anthropogenic components. The satellite focus is on the “A-Train,” a constellation of six spacecraft that will fly in formation from about 2005 to 2008. Key satellite instruments for this report are the Moderate Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES) radiometers on Aqua, the Ozone Monitoring Instrument (OMI) radiometer on Aura, the Polarization and Directionality of Earth's Reflectances (POLDER) polarimeter on the Polarization and Anistropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar (PARASOL), and the Cloud and Aerosol Lider with Orthogonal Polarization (CALIOP) lidar on the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). This strategy is offered as an initial framework—subject to improvement over time—for scientists around the world to participate in the A-Train opportunity. It is a specific implementation of the Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) program, presented earlier in this journal, which identified the integration of diverse data as the central challenge to progress in quantifying global-scale aerosol effects. By designing a strategy around this need for integration, we develop recommendations for both satellite data interpretation and correlative suborbital activities that represent, in many respects, departures from current practice

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Learners’ strategy use has been widely researched over the past few decades. However, studies which focus on the impact of strategy instruction on strategy use, and how far learners of different proficiency levels are able to use the strategies taught in an effective manner, are somewhat rare. The focus of this paper is the impact of writing strategy instruction on writing strategy use of a group of 12 second language learners learning to write in English for Academic Purposes classes. Stimulated recall was used to explore whether this impact differed according to the proficiency level of the students, and revealed that for both high and low proficiency learners’ strategy use developed as a result of the instruction. The implications of these findings for strategy instruction design are discussed

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It has been suggested that Assessment for Learning (AfL) plays a significant role in enhancing teaching and learning in mainstream educational contexts. However, little empirical evidence can support these claims. As AfL has been shown to be enacted predominantly through interactions in primary classes, there is a need to understand if it is appropriate, whether it can be efficiently used in teaching English to Young Learners (TEYL) and how it can facilitate learning in such a context. This emerging research focus gains currency especially in the light of SLA research, which suggests the important role of interactions in foreign language learning. This mixed-method, descriptive and exploratory study aims to investigate how teachers of learners aged 7-11 understand AfL; how they implement it; and the impact that such implementation could have on interactions which occur during lessons. The data were collected through lesson observations, scrutiny of school documents, semi-structured interviews and a focus group interview with teachers. The findings indicate that fitness for purpose guides the implementation of AfL in TEYL classrooms. Significantly, the study has revealed differences in the implementation of AfL between classes of 7-9 and 10-11 year olds within each of the three purposes (setting objectives and expectations; monitoring performance; and checking achievement) identified through the data. Another important finding of this study is the empirical evidence suggesting that the use of AfL could facilitate creating conditions conducive to learning in TEYL classes during collaborative and expert/novice interactions. The findings suggest that teachers’ understanding of AfL is largely aligned with the theoretical frameworks (Black & Wiliam, 2009; Swaffield, 2011) already available. However, they also demonstrate that there are TEYL specific characteristics. This research has important pedagogical implications and indicates a number of areas for further research.

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Schools have a legal duty to make reasonable adjustments for disabled pupils who experience barriers to learning. Inclusive approaches to data collection ensure that the needs of all children who are struggling are not overlooked. However, it is important that the methods promote sustained reflection on the part of all children, do not inadvertently accentuate differences between pupils, and do not allow individual needs to go unrecognized. This paper examines more closely the processes involved in using Nominal Group Technique to collect the views of children with and without a disability on the difficulties experienced in school. Data were collected on the process as well as the outcomes of using this technique to examine how pupil views are transformed from the individual to the collective, a process that involves making the private, public. Contrasts are drawn with questionnaire data, another method of data collection favoured by teachers. Although more time-efficient this can produce unclear and cursory responses. The views that surface from pupils need also to be seen within the context of the ways in which schools customize the data collection process and the ways in which the format and organization of the activity impact on the responses and responsiveness of the pupils.

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Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.

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Among lampyrids, intraspecific sexual communication is facilitated by spectral correspondence between visual sensitivity and bioluminescence emission from the single lantern in the tail. Could a similar strategy be utilized by the elaterids (click beetles), which have one ventral abdominal and two dorsal prothoracic lanterns? Spectral sensitivity [S(lambda)] and bioluminescence were investigated in four Brazilian click beetle species Fulgeochlizus bruchii, Pyrearinus termitilluminans, Pyrophorus punctatissimus and P. divergens, representing three genera. In addition, in situ microspectrophotometric absorption spectra were obtained for visual and screening pigments in P. punctatissimus and P. divergens species. In all species, the electroretinographic S(lambda) functions showed broad peaks in the green with a shoulder in the near-ultraviolet, suggesting the presence of short- and long-wavelength receptors in the compound eyes. The long-wavelength receptor in Pyrophorus species is mediated by a P540 rhodopsin in conjunction with a species-specific screening pigment. A correspondence was found between green to yellow bioluminescence emissions and its broad S(lambda) maximum in each of the four species. It is hypothesized that in elaterids, bioluminescence of the abdominal lantern is an optical signal for intraspecifc sexual communication, while the signals from the prothoracic lanterns serve to warn predators and may also provide illumination in flight.

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This project is based on Artificial Intelligence (A.I) and Digital Image processing (I.P) for automatic condition monitoring of sleepers in the railway track. Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway track infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required.Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the railway track searching for sleeper anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. Hence, it is desired to automate such intuitive human skills for the development of more robust and reliable testing methods. Images of wooden sleepers have been used as data for my project. The aim of this project is to present a vision based technique for inspecting railway sleepers (wooden planks under the railway track) by automatic interpretation of Non Destructive Test (NDT) data using A.I. techniques in determining the results of inspection.

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Since last two decades researches have been working on developing systems that can assistsdrivers in the best way possible and make driving safe. Computer vision has played a crucialpart in design of these systems. With the introduction of vision techniques variousautonomous and robust real-time traffic automation systems have been designed such asTraffic monitoring, Traffic related parameter estimation and intelligent vehicles. Among theseautomatic detection and recognition of road signs has became an interesting research topic.The system can assist drivers about signs they don’t recognize before passing them.Aim of this research project is to present an Intelligent Road Sign Recognition System basedon state-of-the-art technique, the Support Vector Machine. The project is an extension to thework done at ITS research Platform at Dalarna University [25]. Focus of this research work ison the recognition of road signs under analysis. When classifying an image its location, sizeand orientation in the image plane are its irrelevant features and one way to get rid of thisambiguity is to extract those features which are invariant under the above mentionedtransformation. These invariant features are then used in Support Vector Machine forclassification. Support Vector Machine is a supervised learning machine that solves problemin higher dimension with the help of Kernel functions and is best know for classificationproblems.

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Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

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With the rapid advancement of the webtechnology, more and more educationalresources, including software applications forteaching/learning methods, are available acrossthe web, which enables learners to access thelearning materials and use various ways oflearning at any time and any place. Moreover,various web-based teaching/learning approacheshave been developed during the last decade toenhance the capability of both educators andlearners. Particularly, researchers from bothcomputer science and education are workingtogether, collaboratively focusing ondevelopment of pedagogically enablingtechnologies which are believed to improve theinfrastructure of education systems andprocesses, including curriculum developmentmodels, teaching/learning methods, managementof educational resources, systematic organizationof communication and dissemination ofknowledge and skills required by and adapted tousers. Despite of its fast development, however,there are still great gaps between learningintentions, organization of supporting resources,management of educational structures,knowledge points to be learned and interknowledgepoint relationships such as prerequisites,assessment of learning outcomes, andtechnical and pedagogic approaches. Moreconcretely, the issues have been widelyaddressed in literature include a) availability andusefulness of resources, b) smooth integration ofvarious resources and their presentation, c)learners’ requirements and supposed learningoutcomes, d) automation of learning process interms of its schedule and interaction, and e)customization of the resources and agilemanagement of the learning services for deliveryas well as necessary human interferences.Considering these problems and bearing in mindthe advanced web technology of which weshould make full use, in this report we willaddress the following two aspects of systematicarchitecture of learning/teaching systems: 1)learning objects – a semantic description andorganization of learning resources using the webservice models and methods, and 2) learningservices discovery and learning goals match foreducational coordination and learning serviceplanning.

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Denna studie grundar sig i ett uppdrag från Trafikverket med avsikten att undersöka hur enmångfaldsstrategi kan få ökad effekt i organisationen. Utgångspunkten för denna studie är attdet tycks krävas mer forskning kring hur HR strategiskt kan arbeta med mångfaldsfrågor ochintegrera dem i organisationens alla delar. Syftet med denna studie är således att identifiera hurHR strategiskt kan arbeta med mångfaldsfrågor. Vidare är syftet att visa hur ett strategiskamångfaldsarbete kan bli mer effektivt.Teorier som belyser begreppet mångfald, effekterna av mångfald, strategi, Human ResourceManagement och Strategic Human Resource management kan ses ligga till grund för ettframgångsrikt HRM-arbete med mångfald. Ledarskap, kommunikation, kunskap och att se tillorganisationskulturen belyser teorin som viktiga komponenter för att ett strategiskt arbete skabli mer effektivt och ge effekt i organisationen.Studien bygger på en deduktiv ansats och en kvalitativ metod har genomförts utifrån treindividuella intervjuer och två fokusgrupper. De individuella intervjuernas syfte var att belysaorganisationens nutida arbete med mångfald, framtida perspektiv för hur ett strategisktmångfaldsarbete kan utformas och en målbild för vad arbetet ska resultera i. Den enafokusgruppen bestod av medarbetare från HR från olika regionkontor i landet och hade somsyfte att klargöra hur HR strategiskt kan arbeta med mångfald. Den andra fokusgruppen bestodav chefer från olika regionkontor i landet och hade som syfte att belysa chefers roll och vad deeftersöker i ett strategiskt mångfaldsarbete.Resultatet från intervjuerna har analyserats utifrån den teoretiska referensramen och i dennastudie har vi kommit fram till och identifierat flera betydelsefulla faktorer som för HR är viktigai utformandet av en mångfaldsstrategi. Det är viktigt att definiera begreppet mångfald, klargöraansvarsfrågan, visa på varför organisationen bör arbeta med månglad och kommuniceraeffekterna. Vidare är det viktigt att koppla mångfaldsstrategin till övriga HRM-aktiviteter ochorganisationens övriga strategier och mål för att det strategiska arbetet ska ge effekt. Kunskapom mångfald och att se arbetet som ett förändringsarbete där ledningen utgör en viktig roll harvisat sig vara väsentliga faktorer för att arbetet ska få värde i organisationen.