876 resultados para Convolution Product


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Experience underlies all kinds of human knowledge and it is dependent on context. People’s experience within a particular context-of-use determines how they interact with products. Methods employed in this research to elicit human experience have included the use of visuals. This paper describes two empirical studies that employed visual representation of concepts as a means to explore the experiential and contextual component of user- product interactions. One study employed visuals that the participants produced during the study. The other employed visuals that the researcher used as prompts during a focus group session. This paper demonstrates that using visuals in design research is valuable for exploring and understanding the contextual aspects of human experience and its influence on people’s concepts of product use.

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Six sigma has proven itself as a major quality initiative in the last two decades. It is a philosophy which provides a systematic approach to applying numerous tools in the framework of several quality improvement methodologies. The most widely used six sigma methodology is DMAIC, which is best suited for improving existing processes. In order to build quality into the product or service, a proactive approach like Design for Six Sigma (DFSS) is required. This paper provides an overview of DFSS, product innovation, and service innovation. The emphasis is on comparing how DFSS is applied differently in product and service innovation. This paper contributes by analysing the existing literature on DFSS in product and service innovation. The major findings are that the DFSS approach in services and products can be differentiated along the following three dimensions: methodology, characteristics, and technology.

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This paper presents the findings of an investigation of the challenges Australian manufacturers are currently facing. A comprehensive questionnaire survey was conducted among leading Australian manufacturers. This paper reports the main findings of this study. Evidence indicates that product quality and reliability (Q & R) are the main challenges for Australian manufacturers. Design capability and time to market came second. Results show that there is no effective information exchange between the parties involved in production and quality control. Learning from the past mistakes is not proving to have significant effects on improving product quality. The technological innovation speed is high and companies are introducing as many as 5 new products in a year. This technological speed has pressure on the Q & R of new products. To overcome the new challenges, companies need a Q & R improvement model.

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The educational unit new product development, taught within the industrial design program at the Queensland University of Technology (QUT) introduces the relationship between product design and commercialisation to third year industrial design undergraduate students. In which, they are exposed for the first time to product strategy development aimed at meeting consumer expectations, whilst at the same time achieving corporate objectives. Delivered content such as intellectual property, market opportunities, competitor analysis and investor requirements are taught within the thirteen week semester timeframe. New product development theory is not a new field. However, the design approach to teaching this theory and more importantly how designers can use it in the design process is novel. This paper provides an overview of the curriculum design of this unit as well as its incremental development over the past four year duration period. Student project outcomes and more importantly the process and tools from this unit are also discussed and presented.

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The existing Collaborative Filtering (CF) technique that has been widely applied by e-commerce sites requires a large amount of ratings data to make meaningful recommendations. It is not directly applicable for recommending products that are not frequently purchased by users, such as cars and houses, as it is difficult to collect rating data for such products from the users. Many of the e-commerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user's query are retrieved and recommended to the user. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their online navigation behaviour. This paper proposes to integrate collaborative filtering and search-based techniques to provide personalized recommendations for infrequently purchased products. Two different techniques are proposed, namely CFRRobin and CFAg Query. Instead of using the target user's query to search for products as normal search based systems do, the CFRRobin technique uses the products in which the target user's neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAg Query technique uses the products that the user's neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAg Query perform better than the standard Collaborative Filtering (CF) and the Basic Search (BS) approaches, which are widely applied by the current e-commerce applications. The CFRRobin and CFAg Query approaches also outperform the e- isting query expansion (QE) technique that was proposed for recommending infrequently purchased products.

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Anthropometry has long been used for a range of ergonomic applications & product design. Although products are often designed for specific cohorts, anthropometric data are typically sourced from large scale surveys representative of the general population. Additionally, few data are available for emerging markets like China and India. This study measured 80 Chinese males that were representative of a specific cohort targeted for the design of a new product. Thirteen anthropometric measurements were recorded and compared to two large databases that represented a general population, a Chinese database and a Western database. Substantial differences were identified between the Chinese males measured in this study and both databases. The subjects were substantially taller, heavier and broader than subjects in the older Chinese database. However, they were still substantially smaller, lighter and thinner than Western males. Data from current Western anthropometric surveys are unlikely to accurately represent the target population for product designers and manufacturers in emerging markets like China.

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The character of James Bond for many people is intrinsically linked in their minds with particular brands – Aston Martin, Bollinger, Omega, Smirnoff vodka, and so on. This direct association between character and brand highlights the intrinsic role of product placement in the film industry, and in the James Bond films in particular. Selling James Bond: Product Placement in the James Bond Films provides a comprehensive overview of the history of product placement in the James Bond series – charting the progression of the practice and drawing direct correlations to significant cultural and historical events that impacted upon the number and types of products incorporated into the series. While primarily a financial arrangement, it is also important that the practice of product placement be examined and understood in relation to these cultural contexts, an area of research so far largely ignored by academic study. Through extensive content analysis of the official James Bond film series, as well as utilising directors’ commentary and industry reports, this book illustrates the strong impact specific cultural and historical events have had on the practice of product placement in the series. In doing so, it provides an exciting and in-depth “behind the scenes” look at the James Bond film series, and its complicated and sometimes contentious history of product placement. In the process, it charts the gradual emergence of product placement from the more traditional background shot to becoming so embedded in the actual film narrative that they have become simply yet another method for filmmakers to produce cultural meaning.

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This series of research vignettes is aimed at sharing current and interesting findings from our team of international Entrepreneurship researchers. In this vignette, Dr Henri Burgers considers some of the factors that can make a difference in managing new product development.

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One of the key trends that we currently witness not only in academic circles but also in industry - all throughout Australia at least – is that “Innovation” is becoming an important driver for business projects, for change agendas – and in turn, for Business Process Management initiatives.

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This chapter describes a university/high school partnership focused on digital storytelling. It also explains the multi-stage process used to establish this successful partnership and project. The authors discuss the central role that technology played in developing this university/high school partnership, a collaboration that extended the impact of a digital storytelling project to reach high school students, university students, educators, high school administrators, and the local community. Valuing a reflective process that can lead to the creation of a powerful final product, the authors describe the impact of digital storytelling on multiple stakeholders, including the 13 university students and 33 culturally and linguistically diverse high school youth who participated during the fall of 2009. In addition, the chapter includes reflections from university and high school student participants expressed during focus groups conducted throughout the project. While most participants had a positive experience with the project, complications with the technology component often caused frustrations and additional challenges. Goals for sharing this project are to critically evaluate digital storytelling, describe lessons learned, and recommend good practices for others working within a similar context or with parallel goals.

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Positive user experience (UX) has become a key factor in designing interactive products. It acts as a differentiator which can determine a product’s success on the mature market. However, current UX frameworks and methods do not fully support the early stages of product design and development. During these phases, assessment of UX is challenging as no actual user-product interaction can be tested. This qualitative study investigated anticipated user experience (AUX) to address this problem. Using the co-discovery method, participants were asked to imagine a desired product, anticipate experiences with it, and discuss their views with another participant. Fourteen sub-categories emerged from the data, and relationships among them were defined through co-occurrence analysis. These data formed the basis of the AUX framework which consists of two networks which elucidate 1) how users imagine a desired product and 2) how they anticipate positive experiences with that product. Through this AUX framework, important factors in the process of imagining future products and experiences were learnt, including the way in which these factors interrelate. Focusing on and exploring each component of the two networks in the framework will allow designers to obtain a deeper understanding of the required pragmatic and hedonic qualities of product, intended uses of product, user characteristics, potential contexts of experience, and anticipated emotions embedded within the experience. This understanding, in turn, will help designers to better foresee users’ underlying needs and to focus on the most important aspects of their positive experience. Therefore, the use of the AUX framework in the early stages of product development will contribute to the design for pleasurable UX.

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Generic sentiment lexicons have been widely used for sentiment analysis these days. However, manually constructing sentiment lexicons is very time-consuming and it may not be feasible for certain application domains where annotation expertise is not available. One contribution of this paper is the development of a statistical learning based computational method for the automatic construction of domain-specific sentiment lexicons to enhance cross-domain sentiment analysis. Our initial experiments show that the proposed methodology can automatically generate domain-specific sentiment lexicons which contribute to improve the effectiveness of opinion retrieval at the document level. Another contribution of our work is that we show the feasibility of applying the sentiment metric derived based on the automatically constructed sentiment lexicons to predict product sales of certain product categories. Our research contributes to the development of more effective sentiment analysis system to extract business intelligence from numerous opinionated expressions posted to the Web

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With the development of enterprise informatisation, Product Lifecycle Management (PLM) systems have been widely deployed and applied in enterprises. This paper analyzes the requirement that conducting version operations on business objects as specified in process models should be compliant with the versioning policies imposed by product lifecycles. This leads to the introduction of the concept of versioning compliance, and the approach of compliance checking that we proposed in our earlier work, which comprises both syntactical compatibility and behavioural compatibility checking. The paper then focuses on the tool implementation for providing automated support to the versioning compliance checking. An empirical evaluation of the tool was also performed with industrial partners using the well-known questionnaire-based method. The evaluation and feedback from practitioners further evidence the practical significance of this research question in the PLM field and demonstrate that the proposed solution with its automated tool support possesses a high application potential.

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The presence of air and bone interfaces makes the dose distribution for head and neck cancer treatments difficult to accurately predict. This study compared planning system dose calculations using the collapsed-cone convolution algorithm with EGSnrcMonte Carlo simulation results obtained using the Monte Carlo DICOMToolKit software, for one oropharynx, two paranasal sinus and three nodal treatment plans. The difference between median doses obtained from the treatment planning and Monte Carlo calculations was found to be greatest in two bilateral treatments: 4.8%for a retropharyngeal node irradiation and 6.7% for an ethmoid paranasal sinus treatment. These deviations in median dose were smaller for two unilateral treatments: 0.8% for an infraclavicular node irradiation and 2.8% for a cervical node treatment. Examination of isodose distributions indicated that the largest deviations between Monte Carlo simulation and collapsed-cone convolution calculations were seen in the bilateral treatments, where the increase in calculated dose beyond air cavities was most significant.