986 resultados para Computer users
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Esta pesquisa teve por objetivo refletir sobre o ensino instrumental da leitura em inglês, através da utilização de componentes visuais para auxiliar leitores na construção do significado. Com pressupostos teóricos baseados principalmente em Swales (1990); Soares (1993); Bronckart (1999); Joly (2002); Santaella (1983, 2000); Magno e Silva (2002, 2004); e Field (2004), efetuamos um estudo descritivo das características semiótico-discursivas presentes em manuais de instalação de softwares com enfoque nos recursos visuais. Além disso, coletamos dados e descrevemos os procedimentos pedagógicos observados em uma turma de Inglês Instrumental do Curso Superior de Tecnologia em Redes de Computadores, da Faculdade de Tecnologia da Amazônia (FAZ), em Belém. Nossa pesquisa-ação objetivou também investigar em que medida os componentes visuais podem influenciar o leitor nas suas escolhas de leitura; de que forma os componentes visuais podem ser utilizados em atividades de pré-leitura, leitura e pós-leitura para conduzir o leitor à compreensão do sentido do texto; e qual a importância dos componentes visuais na leitura de manuais de instalação de softwares. Os resultados da análise foram sucessivamente alterando a coleta seqüencial dos dados e mostraram que os componentes visuais são excelentes ferramentas que, quando bem utilizadas e associadas às palavras, podem incentivar e simplificar o processamento da leitura, especialmente num contexto em que os participantes não possuem pleno domínio lingüístico na língua-alvo.
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Pós-graduação em Letras - FCLAR
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This report shares my efforts in developing a solid unit of instruction that has a clear focus on student outcomes. I have been a teacher for 20 years and have been writing and revising curricula for much of that time. However, most has been developed without the benefit of current research on how students learn and did not focus on what and how students are learning. My journey as a teacher has involved a lot of trial and error. My traditional method of teaching is to look at the benchmarks (now content expectations) to see what needs to be covered. My unit consists of having students read the appropriate sections in the textbook, complete work sheets, watch a video, and take some notes. I try to include at least one hands-on activity, one or more quizzes, and the traditional end-of-unit test consisting mostly of multiple choice questions I find in the textbook. I try to be engaging, make the lessons fun, and hope that at the end of the unit my students get whatever concepts I‘ve presented so that we can move on to the next topic. I want to increase students‘ understanding of science concepts and their ability to connect understanding to the real-world. However, sometimes I feel that my lessons are missing something. For a long time I have wanted to develop a unit of instruction that I know is an effective tool for the teaching and learning of science. In this report, I describe my efforts to reform my curricula using the “Understanding by Design” process. I want to see if this style of curriculum design will help me be a more effective teacher and if it will lead to an increase in student learning. My hypothesis is that this new (for me) approach to teaching will lead to increased understanding of science concepts among students because it is based on purposefully thinking about learning targets based on “big ideas” in science. For my reformed curricula I incorporate lessons from several outstanding programs I‘ve been involved with including EpiCenter (Purdue University), Incorporated Research Institutions for Seismology (IRIS), the Master of Science Program in Applied Science Education at Michigan Technological University, and the Michigan Association for Computer Users in Learning (MACUL). In this report, I present the methodology on how I developed a new unit of instruction based on the Understanding by Design process. I present several lessons and learning plans I‘ve developed for the unit that follow the 5E Learning Cycle as appendices at the end of this report. I also include the results of pilot testing of one of lessons. Although the lesson I pilot-tested was not as successful in increasing student learning outcomes as I had anticipated, the development process I followed was helpful in that it required me to focus on important concepts. Conducting the pilot test was also helpful to me because it led me to identify ways in which I could improve upon the lesson in the future.
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Using a computer keyboard with the forearms unsupported has been proposed as a causal factor for neck/shoulder and arm/hand diagnoses. Recent laboratory and field studies have demonstrated that forearm support might be preferable to working in the traditional floating posture. The aim of this study was to determine whether providing forearm Support when using a normal computer workstation would decrease musculoskeletal discomfort in intensive computer users in a call centre. A randomised controlled study (n = 59), of 6 weeks duration was conducted. Thirty participants (Group 1) were allocated to forearm support using the desk surface with the remainder (Group 2) acting as a control group. At 6 weeks, the control group was also set up with forearm support. Both groups were then monitored for another 6 weeks. Questionnaires were used at 1, 6 and 12 weeks to obtain information about discomfort, workstation setup, working posture and comfort. Nine participants (Group 1 n = 6, Group 2 n = 3) withdrew within a week of commencing forearm support either due to discomfort or difficulty in maintaining the posture. At 6 weeks, the group using forearm support generated significantly fewer reports of discomfort in the neck and back, although the difference between the groups was not statistically significant. At 12 weeks, there were fewer reports of neck, back and wrist discomfort when preintervention discomfort was compared with post intervention discomfort. These findings indicate that for the majority of users, forearm support may be preferable to the floating Posture implicit in current guidelines for computer workstation setup. (C) 2004 Elsevier Ltd. All rights reserved.
Interaction of psychosocial risk factors explain increased neck problems among female office workers
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This study investigated the relationship between psychosocial risk factors and (1) neck symptoms and (2) neck pain and disability as measured by the neck disability index (NDI). Female office workers employed in local private and public organizations were invited to participate, with 333 completing a questionnaire. Data were collected on various risk factors including age, negative affectivity, history of previous neck trauma, physical work environment, and task demands. Sixty-one percent of the sample reported neck symptoms lasting greater than 8 days in the last 12 months. The mean NDI of the sample was 15.5 out of 100, indicating mild neck pain and disability. In a hierarchical multivariate logistic regression, low supervisor support was the only psychosocial risk factor identified with the presence of neck symptoms. Similarly, low supervisor support was the only factor associated with the score on the NDI. These associations remained after adjustment for potential confounders of age, negative affectivity, and physical risk factors. The interaction of job demands, decision authority, and supervisor support was significantly associated with the NDI in the final model and this association increased when those with previous trauma were excluded. Interestingly, and somewhat contrary to initial expectations, as job demands increased, high decision authority had an increasing effect on the NDI when supervisor support was low. Crown copyright (c) 2006 Published by Elsevier B.V. All rights reserved.
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With the rapid growth of the Internet, computer attacks are increasing at a fast pace and can easily cause millions of dollar in damage to an organization. Detecting these attacks is an important issue of computer security. There are many types of attacks and they fall into four main categories, Denial of Service (DoS) attacks, Probe, User to Root (U2R) attacks, and Remote to Local (R2L) attacks. Within these categories, DoS and Probe attacks continuously show up with greater frequency in a short period of time when they attack systems. They are different from the normal traffic data and can be easily separated from normal activities. On the contrary, U2R and R2L attacks are embedded in the data portions of the packets and normally involve only a single connection. It becomes difficult to achieve satisfactory detection accuracy for detecting these two attacks. Therefore, we focus on studying the ambiguity problem between normal activities and U2R/R2L attacks. The goal is to build a detection system that can accurately and quickly detect these two attacks. In this dissertation, we design a two-phase intrusion detection approach. In the first phase, a correlation-based feature selection algorithm is proposed to advance the speed of detection. Features with poor prediction ability for the signatures of attacks and features inter-correlated with one or more other features are considered redundant. Such features are removed and only indispensable information about the original feature space remains. In the second phase, we develop an ensemble intrusion detection system to achieve accurate detection performance. The proposed method includes multiple feature selecting intrusion detectors and a data mining intrusion detector. The former ones consist of a set of detectors, and each of them uses a fuzzy clustering technique and belief theory to solve the ambiguity problem. The latter one applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The final decision is a combination of the outputs of feature selecting and data mining detectors. The experimental results indicate that our ensemble approach not only significantly reduces the detection time but also effectively detect U2R and R2L attacks that contain degrees of ambiguous information.
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More information is now readily available to computer users than at any time in human history; however, much of this information is often inaccessible to people with blindness or low-vision, for whom information must be presented non-visually. Currently, screen readers are able to verbalize on-screen text using text-to-speech (TTS) synthesis; however, much of this vocalization is inadequate for browsing the Internet. An auditory interface that incorporates auditory-spatial orientation was created and tested. For information that can be structured as a two-dimensional table, links can be semantically grouped as cells in a row within an auditory table, which provides a consistent structure for auditory navigation. An auditory display prototype was tested.^ Sixteen legally blind subjects participated in this research study. Results demonstrated that stereo panning was an effective technique for audio-spatially orienting non-visual navigation in a five-row, six-column HTML table as compared to a centered, stationary synthesized voice. These results were based on measuring the time- to-target (TTT), or the amount of time elapsed from the first prompting to the selection of each tabular link. Preliminary analysis of the TTT values recorded during the experiment showed that the populations did not conform to the ANOVA requirements of normality and equality of variances. Therefore, the data were transformed using the natural logarithm. The repeated-measures two-factor ANOVA results show that the logarithmically-transformed TTTs were significantly affected by the tonal variation method, F(1,15) = 6.194, p= 0.025. Similarly, the results show that the logarithmically transformed TTTs were marginally affected by the stereo spatialization method, F(1,15) = 4.240, p=0.057. The results show that the logarithmically transformed TTTs were not significantly affected by the interaction of both methods, F(1,15) = 1.381, p=0.258. These results suggest that some confusion may be caused in the subject when employing both of these methods simultaneously. The significant effect of tonal variation indicates that the effect is actually increasing the average TTT. In other words, the presence of preceding tones increases task completion time on average. The marginally-significant effect of stereo spatialization decreases the average log(TTT) from 2.405 to 2.264.^
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With the rapid growth of the Internet, computer attacks are increasing at a fast pace and can easily cause millions of dollar in damage to an organization. Detecting these attacks is an important issue of computer security. There are many types of attacks and they fall into four main categories, Denial of Service (DoS) attacks, Probe, User to Root (U2R) attacks, and Remote to Local (R2L) attacks. Within these categories, DoS and Probe attacks continuously show up with greater frequency in a short period of time when they attack systems. They are different from the normal traffic data and can be easily separated from normal activities. On the contrary, U2R and R2L attacks are embedded in the data portions of the packets and normally involve only a single connection. It becomes difficult to achieve satisfactory detection accuracy for detecting these two attacks. Therefore, we focus on studying the ambiguity problem between normal activities and U2R/R2L attacks. The goal is to build a detection system that can accurately and quickly detect these two attacks. In this dissertation, we design a two-phase intrusion detection approach. In the first phase, a correlation-based feature selection algorithm is proposed to advance the speed of detection. Features with poor prediction ability for the signatures of attacks and features inter-correlated with one or more other features are considered redundant. Such features are removed and only indispensable information about the original feature space remains. In the second phase, we develop an ensemble intrusion detection system to achieve accurate detection performance. The proposed method includes multiple feature selecting intrusion detectors and a data mining intrusion detector. The former ones consist of a set of detectors, and each of them uses a fuzzy clustering technique and belief theory to solve the ambiguity problem. The latter one applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The final decision is a combination of the outputs of feature selecting and data mining detectors. The experimental results indicate that our ensemble approach not only significantly reduces the detection time but also effectively detect U2R and R2L attacks that contain degrees of ambiguous information.
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This is a long-term study of the use of information and communication technologies by 30 older adults (ages 70–97) living in a large retirement community. The study spanned the years of 1996 to 2008, during which time the research participants grappled with the challenges of computer use while aging 12 years. The researcher, herself a ‘mature learner,’ used a qualitative research design which included observations and open-ended interviews. Using a strategy of “intermittent immersion,” she spent an average of two weeks per visit on site and participated in the lives of the research population in numerous ways, including service as their computer tutor. With e-mail and telephone contact, she was able to continue her interactions with participants throughout the 12-year period. A long-term perspective afforded the view of the evolution, devolution or cessation of the technology use by these older adults, and this process is chronicled in detail through five individual “profiles.” Three research questions dominated the inquiry: What function do computers serve in the lives of older adults? Does computer use foster or interfere with social ties? Is social support necessary for success in the face of challenging learning tasks? In answer to the first question, it became clear that computers were valued as a symbol of competence and intelligence. Some individuals brought their computers with them when transferred to the single-room residences of assisted living or nursing care facilities. Even when use had ceased, their computers were displayed to signal that their owners were or had once been keeping up to date. In answer to the second question, computer owners socialized around computing use (with in-person family members or friends) more than, or as much as, they socialized through their computers in the digital realm of the Internet. And in answer to the third question, while the existence of social support did facilitate computer exploration, more important was the social support network generated and developed among fellow computer users.
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Research on the criminological side of system trespassing (i.e. unlawfully gaining access to a computer system) is relatively rare and has yet to examine the effect of the presence of other users on the system during the trespassing event (i.e. the time of communication between a trespasser’s system and the infiltrated system). This thesis seeks to analyze this relationship drawing on principles of Situational Crime Prevention, Routine Activities Theory, and restrictive deterrence. Data were collected from a randomized control trial of target computers deployed on the Internet network of a large U.S. university. This study examined whether the number (one or multiple) and type (administrative or non-administrative) of computer users present on a system reduced the seriousness and frequency of trespassing. Results indicated that the type of user (administrative) produced a restrictive deterrent effect and significantly reduced the frequency and duration of trespassing events.
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This thesis aimed at addressing some of the issues that, at the state of the art, avoid the P300-based brain computer interface (BCI) systems to move from research laboratories to end users’ home. An innovative asynchronous classifier has been defined and validated. It relies on the introduction of a set of thresholds in the classifier, and such thresholds have been assessed considering the distributions of score values relating to target, non-target stimuli and epochs of voluntary no-control. With the asynchronous classifier, a P300-based BCI system can adapt its speed to the current state of the user and can automatically suspend the control when the user diverts his attention from the stimulation interface. Since EEG signals are non-stationary and show inherent variability, in order to make long-term use of BCI possible, it is important to track changes in ongoing EEG activity and to adapt BCI model parameters accordingly. To this aim, the asynchronous classifier has been subsequently improved by introducing a self-calibration algorithm for the continuous and unsupervised recalibration of the subjective control parameters. Finally an index for the online monitoring of the EEG quality has been defined and validated in order to detect potential problems and system failures. This thesis ends with the description of a translational work involving end users (people with amyotrophic lateral sclerosis-ALS). Focusing on the concepts of the user centered design approach, the phases relating to the design, the development and the validation of an innovative assistive device have been described. The proposed assistive technology (AT) has been specifically designed to meet the needs of people with ALS during the different phases of the disease (i.e. the degree of motor abilities impairment). Indeed, the AT can be accessed with several input devices either conventional (mouse, touchscreen) or alterative (switches, headtracker) up to a P300-based BCI.
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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.
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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.