17 resultados para Chinese information processing

em Aston University Research Archive


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This paper complements earlier work by the author that shows that the pattern of information arrivals into the UK stock market may explain the behaviour of returns. It is argued that delays or other systematic behaviour in the processing of this information could compound the impact of information arrival patterns. It is found, however, that this does not happen, and so it is the arrival and not the processing of news that is most important. © 2004 Taylor & Francis Ltd.

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With the extensive use of pulse modulation methods in telecommunications, much work has been done in the search for a better utilisation of the transmission channel.The present research is an extension of these investigations. A new modulation method, 'Variable Time-Scale Information Processing', (VTSIP), is proposed.The basic principles of this system have been established, and the main advantages and disadvantages investigated. With the proposed system, comparison circuits detect the instants at which the input signal voltage crosses predetermined amplitude levels.The time intervals between these occurrences are measured digitally and the results are temporarily stored, before being transmitted.After reception, an inverse process enables the original signal to be reconstituted.The advantage of this system is that the irregularities in the rate of information contained in the input signal are smoothed out before transmission, allowing the use of a smaller transmission bandwidth. A disadvantage of the system is the time delay necessarily introduced by the storage process.Another disadvantage is a type of distortion caused by the finite store capacity.A simulation of the system has been made using a standard speech signal, to make some assessment of this distortion. It is concluded that the new system should be an improvement on existing pulse transmission systems, allowing the use of a smaller transmission bandwidth, but introducing a time delay.

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This thesis examines children's consumer choice behaviour using an information processing perspective, with the fundamental goal of applying academic research to practical marketing and commercial problems. Proceeding a preface, which describes the academic and commercial terms of reference within which this interdisciplinary study is couched, the thesis comprises four discernible parts. Initially, the rationale inherent in adopting an information processing perspective is justified and the diverse array of topics which have bearing on children's consumer processing and behaviour are aggregated. The second part uses this perspective as a springboard to appraise the little explored role of memory, and especially memory structure, as a central cognitive component in children's consumer choice processing. The main research theme explores the ease with which 10 and 11 year olds retrieve contemporary consumer information from subjectively defined memory organisations. Adopting a sort-recall paradigm, hierarchical retrieval processing is stimulated and it is contended that when two items, known to be stored proximally in the memory organisation are not recalled adjacently, this discrepancy is indicative of retrieval processing ease. Results illustrate the marked influence of task conditions and orientation of memory structure on retrieval; these conclusions are accounted for in terms of input and integration failure. The third section develops the foregoing interpellations in the marketing context. A straightforward methodology for structuring marketing situations is postulated, a basis for segmenting children's markets using processing characteristics is adopted, and criteria for communicating brand support information to children are discussed. A taxonomy of market-induced processing conditions is developed. Finally, a case study with topical commercial significance is described. The development, launch and marketing of a new product in the confectionery market is outlined, the aetiology of its subsequent demise identified and expounded, and prescriptive guidelines are put forward to help avert future repetition of marketing misjudgements.

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For over 30. years information-processing approaches to leadership and more specifically Implicit Leadership Theories (ILTs) research has contributed a significant body of knowledge on leadership processes in applied settings. A new line of research on Implicit Followership Theories (IFTs) has re-ignited interest in information-processing and socio-cognitive approaches to leadership and followership. In this review, we focus on organizational research on ILTs and IFTs and highlight their practical utility for the exercise of leadership and followership in applied settings. We clarify common misperceptions regarding the implicit nature of ILTs and IFTs, review both direct and indirect measures, synthesize current and ongoing research on ILTs and IFTs in organizational settings, address issues related to different levels of analysis in the context of leadership and follower schemas and, finally, propose future avenues for organizational research. © 2013 Elsevier Inc.

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Three studies tested the impact of properties of behavioral intention on intention-behavior consistency, information processing, and resistance. Principal components analysis showed that properties of intention formed distinct factors. Study 1 demonstrated that temporal stability, but not the other intention attributes, moderated intention-behavior consistency. Study 2 found that greater stability of intention was associated with improved memory performance. In Study 3, participants were confronted with a rating scale manipulation designed to alter their intention scores. Findings showed that stable intentions were able to withstand attack. Overall, the present research findings suggest that different properties of intention are not simply manifestations of a single underlying construct ("intention strength"), and that temporal stability exhibits superior resistance and impact compared to other intention attributes. © 2013 Wiley Periodicals, Inc.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

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As one of the most popular deep learning models, convolution neural network (CNN) has achieved huge success in image information extraction. Traditionally CNN is trained by supervised learning method with labeled data and used as a classifier by adding a classification layer in the end. Its capability of extracting image features is largely limited due to the difficulty of setting up a large training dataset. In this paper, we propose a new unsupervised learning CNN model, which uses a so-called convolutional sparse auto-encoder (CSAE) algorithm pre-Train the CNN. Instead of using labeled natural images for CNN training, the CSAE algorithm can be used to train the CNN with unlabeled artificial images, which enables easy expansion of training data and unsupervised learning. The CSAE algorithm is especially designed for extracting complex features from specific objects such as Chinese characters. After the features of articficial images are extracted by the CSAE algorithm, the learned parameters are used to initialize the first CNN convolutional layer, and then the CNN model is fine-Trained by scene image patches with a linear classifier. The new CNN model is applied to Chinese scene text detection and is evaluated with a multilingual image dataset, which labels Chinese, English and numerals texts separately. More than 10% detection precision gain is observed over two CNN models.

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We propose a novel all-optical signal processor for use at a return-to-zero receiver utilising loop mirror intensity filtering and nonlinear pulse broadening in normal dispersion fibre. The device offers reamplification and cleaning up of the optical signals, and phase margin improvement. The efficiency of the technique is demonstrated by application to 40 Gbit/s data transmission.

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Modern managers are under tremendous pressure in attempting to fulfil a profoundly complex managerial task, that of handling information resources. Information management, an intricate process requiring a high measure of human cognition and discernment, involves matching a manager's lack of information processing capacity against his information needs, with voluminous information at his disposal. The nature of the task will undoubtedly become more complex in the case of a large organisation. Management of large-scale organisations is therefore an exceedingly challenging prospect for any manager to be faced with. A system that supports executive information needs will help reduce managerial and informational mismatches. In the context of the Malaysian public sector, the task of overall management lies with the Prime Minister and the Cabinet. The Prime Minister's Office is presently supporting the Prime Minister's information and managerial needs, although not without various shortcomings. The rigid formalised structure predominant of the Malaysian public sector, so opposed to dynamic treatment of problematic issues as faced by that sector, further escalates the managerial and organisational problem of coping with a state of complexity. The principal features of the research are twofold: the development of a methodology for diagnosing the problem organisation' and the design of an office system. The methodological development is done in the context of the Malaysian public sector, and aims at understanding the complexity of its communication and control situation. The outcome is a viable model of the public sector. `Design', on the other hand, is developing a syntax or language for office systems which provides an alternative to current views on office systems. The design is done with reference to, rather than for, the Prime Minister's Office. The desirable outcome will be an office model called Office Communication and Information System (OCIS).

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Improving bit error rates in optical communication systems is a difficult and important problem. The error correction must take place at high speed and be extremely accurate. We show the feasibility of using hardware implementable machine learning techniques. This may enable some error correction at the speed required.

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Huge advertising budgets are invested by firms to reach and convince potential consumers to buy their products. To optimize these investments, it is fundamental not only to ensure that appropriate consumers will be reached, but also that they will be in appropriate reception conditions. Marketing research has focused on the way consumers react to advertising, as well as on some individual and contextual factors that could mediate or moderate the ad impact on consumers (e.g. motivation and ability to process information or attitudes toward advertising). Nevertheless, a factor that potentially influences consumers’ advertising reactions has not yet been studied in marketing research: fatigue. Fatigue can yet impact key variables of advertising processing, such as cognitive resources availability (Lieury 2004). Fatigue is felt when the body warns to stop an activity (or inactivity) to have some rest, allowing the individual to compensate for fatigue effects. Dittner et al. (2004) defines it as “the state of weariness following a period of exertion, mental or physical, characterized by a decreased capacity for work and reduced efficiency to respond to stimuli.’’ It signals that resources will lack if we continue with the ongoing activity. According to Schmidtke (1969), fatigue leads to troubles in information reception, in perception, in coordination, in attention getting, in concentration and in thinking. In addition, for Markle (1984) fatigue generates a decrease in memory, and in communication ability, whereas it increases time reaction, and number of errors. Thus, fatigue may have large effects on advertising processing. We suggest that fatigue determines the level of available resources. Some research about consumer responses to advertising claim that complexity is a fundamental element to take into consideration. Complexity determines the cognitive efforts the consumer must provide to understand the message (Putrevu et al. 2004). Thus, we suggest that complexity determines the level of required resources. To study this complex question about need and provision of cognitive resources, we draw upon Resource Matching Theory. Anand and Sternthal (1989, 1990) are the first to state the Resource Matching principle, saying that an ad is most persuasive when the resources required to process it match the resources the viewer is willing and able to provide. They show that when the required resources exceed those available, the message is not entirely processed by the consumer. And when there are too many available resources comparing to those required, the viewer elaborates critical or unrelated thoughts. According to the Resource Matching theory, the level of resource demanded by an ad can be high or low, and is mostly determined by the ad’s layout (Peracchio and Myers-Levy, 1997). We manipulate the level of required resources using three levels of ad complexity (low – high – extremely high). On the other side, the resource availability of an ad viewer is determined by lots of contextual and individual variables. We manipulate the level of available resources using two levels of fatigue (low – high). Tired viewers want to limit the processing effort to minimal resource requirements by making heuristics, forming overall impression at first glance. It will be easier for them to decode the message when ads are very simple. On the contrary, the most effective ads for viewers who are not tired are complex enough to draw their attention and fully use their resources. They will use more analytical strategies, looking at the details of the ad. However, if ads are too complex, they will be too difficult to understand. The viewer will be discouraged to process information and will overlook the ad. The objective of our research is to study fatigue as a moderating variable of advertising information processing. We run two experimental studies to assess the effect of fatigue on visual strategies, comprehension, persuasion and memorization. In study 1, thirty-five undergraduate students enrolled in a marketing research course participated in the experiment. The experimental design is 2 (tiredness level: between subjects) x 3 (ad complexity level: within subjects). Participants were randomly assigned a schedule time (morning: 8-10 am or evening: 10-12 pm) to perform the experiment. We chose to test subjects at various moments of the day to obtain maximum variance in their fatigue level. We use Morningness / Eveningness tendency of participants (Horne & Ostberg, 1976) as a control variable. We assess fatigue level using subjective measures - questionnaire with fatigue scales - and objective measures - reaction time and number of errors. Regarding complexity levels, we have designed our own ads in order to keep aspects other than complexity equal. We ran a pretest using the Resource Demands scale (Keller and Bloch 1997) and by rating them on complexity like Morrison and Dainoff (1972) to check for our complexity manipulation. We found three significantly different levels. After having completed the fatigue scales, participants are asked to view the ads on a screen, while their eye movements are recorded by the eye-tracker. Eye-tracking allows us to find out patterns of visual attention (Pieters and Warlop 1999). We are then able to infer specific respondents’ visual strategies according to their level of fatigue. Comprehension is assessed with a comprehension test. We collect measures of attitude change for persuasion and measures of recall and recognition at various points of time for memorization. Once the effect of fatigue will be determined across the student population, it is interesting to account for individual differences in fatigue severity and perception. Therefore, we run study 2, which is similar to the previous one except for the design: time of day is now within-subjects and complexity becomes between-subjects