435 resultados para Senjie Lin


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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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Providing a positive user experience (UX) has become the key differentiator for products to win a competition in mature markets. To ensure that a product will support enjoyable experiences for its users, assessment of UX should be conducted early during the design and development process. However, most UX frameworks and evaluation techniques focus on understanding and assessing user’s experience with functional prototypes or existing products. This situation delays UX assessment until the late phases of product development which may result in costly design modifications and less desirable products. A qualitative study was conducted to investigate anticipated user experience (AUX) to address this issue. Twenty pairs of participants were asked to imagine an interactive product, draw their product concept, and anticipate their interactions and experiences with it. The data was analyzed to identify general characteristics of AUX. We found that while positive AUX was mostly related to an imagined/desired product, negative AUX was mainly associated with existing products. It was evident that the pragmatic quality of product was fundamental, and significantly influenced user’s anticipated experiences. Furthermore, the hedonic quality of product received more focus in positive than negative AUX. The results also showed that context, user profile, experiential knowledge, and anticipated emotion could be reflected in AUX. The understanding of AUX will help product designers to better foresee the users’ underlying needs and to focus on the most important aspects of their positive experiences, which in turn facilitates the designers to ensure pleasurable UX from the start of the design process.

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Iron (Fe) is the fourth most abundant element in the Earth’s crust. Excess Fe mobilization from terrestrial into aquatic systems is of concern for deterioration of water quality via biofouling and nuisance algal blooms in coastal and marine systems. Substantial Fe dissolution and transport involve alternate Fe(II) oxidation followed by Fe(III) reduction, with a diversity of Bacteria and Archaea acting as the key catalyst. Microbially-mediated Fe cycling is of global significance with regard to cycles of carbon (C), sulfur (S) and manganese (Mn). However, knowledge regarding microbial Fe cycling in circumneutral-pH habitats that prevail on Earth has been lacking until recently. In particular, little is known regarding microbial function in Fe cycling and associated Fe mobilization and greenhouse (CO2 and CH4, GHG) evolution in subtropical Australian coastal systems where microbial response to ambient variations such as seasonal flooding and land use changes is of concern. Using the plantation-forested Poona Creek catchment on the Fraser Coast of Southeast Queensland (SEQ), this research aimed to 1) study Fe cycling-associated bacterial populations in diverse terrestrial and aquatic habitats of a representative subtropical coastal circumneutral-pH (4–7) ecosystem; and 2) assess potential impacts of Pinus plantation forestry practices on microbially-mediated Fe mobilization, organic C mineralization and associated GHG evolution in coastal SEQ. A combination of wet-chemical extraction, undisturbed core microcosm, laboratory bacterial cultivation, microscopy and 16S rRNA-based molecular phylogenetic techniques were employed. The study area consisted primarily of loamy sands, with low organic C and dissolved nutrients. Total reactive Fe was abundant and evenly distributed within soil 0–30 cm profiles. Organic complexation primarily controlled Fe bioavailability and forms in well-drained plantation soils and water-logged, native riparian soils, whereas tidal flushing exerted a strong “seawater effect” in estuarine locations and formed a large proportion of inorganic Fe(III) complexes. There was a lack of Fe(II) sources across the catchment terrestrial system. Mature, first-rotation plantation clear-felling and second-rotation replanting significantly decreased organic matter and poorly crystalline Fe in well-drained soils, although variations in labile soil organic C fractions (dissolved organic C, DOC; and microbial biomass C, MBC) were minor. Both well-drained plantation soils and water-logged, native-vegetation soils were inhabited by a variety of cultivable, chemotrophic bacterial populations capable of C, Fe, S and Mn metabolism via lithotrophic or heterotrophic, (micro)aerobic or anaerobic pathways. Neutrophilic Fe(III)-reducing bacteria (FeRB) were most abundant, followed by aerobic, heterotrophic bacteria (heterotrophic plate count, HPC). Despite an abundance of FeRB, cultivable Fe(II)-oxidizing bacteria (FeOB) were absent in associated soils. A lack of links between cultivable Fe, S or Mn bacterial densities and relevant chemical measurements (except for HPC correlated with DOC) was likely due to complex biogeochemical interactions. Neither did variations in cultivable bacterial densities correlate with plantation forestry practices, despite total cultivable bacterial densities being significantly lower in estuarine soils when compared with well-drained plantation soils and water-logged, riparian native-vegetation soils. Given that bacterial Fe(III) reduction is the primary mechanism of Fe oxide dissolution in soils upon saturation, associated Fe mobilization involved several abiotic and biological processes. Abiotic oxidation of dissolved Fe(II) by Mn appeared to control Fe transport and inhibit Fe dissolution from mature, first-rotation plantation soils post-saturation. Such an effect was not observed in clear-felled and replanted soils associated with low SOM and potentially low Mn reactivity. Associated GHG evolution post-saturation mainly involved variable CO2 emissions, with low, but consistently increasing CH4 effluxes in mature, first-rotation plantation soil only. In comparison, water-logged soils in the riparian native-vegetation buffer zone functioned as an important GHG source, with high potentials for Fe mobilization and GHG, particularly CH4 emissions in riparian loam soils associated with high clay and crystalline Fe fractions. Active Fe–C cycling was unlikely to occur in lower-catchment estuarine soils associated with low cultivable bacterial densities and GHG effluxes. As a key component of bacterial Fe cycling, neutrophilic FeOB widely occurred in diverse aquatic, but not terrestrial, habitats of the catchment study area. Stalked and sheathed FeOB resembling Gallionella and Leptothrix were limited to microbial mat material deposited in surface fresh waters associated with a circumneutral-pH seep, and clay-rich soil within riparian buffer zones. Unicellular, Sideroxydans-related FeOB (96% sequence identity) were ubiquitous in surface and subsurface freshwater environments, with highest abundance in estuary-adjacent shallow coastal groundwater water associated with redox transition. The abundance of dissolved C and Fe in the groundwater-dependent system was associated with high numbers of cultivable anaerobic, heterotrophic FeRB, microaerophilic, putatively lithotrophic FeOB and aerobic, heterotrophic bacteria. This research represents the first study of microbial Fe cycling in diverse circumneutral-pH environments (terrestrial–aquatic, freshwater–estuarine, surface–subsurface) of a subtropical coastal ecosystem. It also represents the first study of its kind in the southern hemisphere. This work highlights the significance of bacterial Fe(III) reduction in terrestrial, and bacterial Fe(II) oxidation in aquatic catchment Fe cycling. Results indicate the risk of promotion of Fe mobilization due to plantation clear-felling and replanting, and GHG emissions associated with seasonal water-logging. Additional significant outcomes were also achieved. The first direct evidence for multiple biomineralization patterns of neutrophilic, microaerophilic, unicellular FeOB was presented. A putatively pure culture, which represents the first cultivable neutrophilic FeOB from the southern hemisphere, was obtained as representative FeOB ubiquitous in diverse catchment aquatic habitats.

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Differential pulse stripping voltammetry method(DPSV) was applied to the determination of three herbicides, ametryn, cyanatryn, and dimethametryn. It was found that their voltammograms overlapped strongly, and it is difficult to determine these compounds individually from their mixtures. With the aid of chemometrics, classical least squares(CLS), principal component regression(PCR) and partial least squares(PLS), voltammogram resolution and quantitative analysis of the synthetic mixtures of the three compounds were successfully performed. The proposed method was also applied to the analysis of some real samples with satisfactory results.

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Failing injectors are one of the most common faults in diesel engines. The severity of these faults could have serious effects on diesel engine operations such as engine misfire, knocking, insufficient power output or even cause a complete engine breakdown. It is thus essential to prevent such faults from occurring by monitoring the condition of these injectors. In this paper, the authors present the results of an experimental investigation on identifying the signal characteristics of a simulated incipient injector fault in a diesel engine using both in-cylinder pressure and acoustic emission (AE) techniques. A time waveform event driven synchronous averaging technique was used to minimize or eliminate the effect of engine speed variation and amplitude fluctuation. It was found that AE is an effective method to detect the simulated injector fault in both time (crank angle) and frequency (order) domains. It was also shown that the time domain in-cylinder pressure signal is a poor indicator for condition monitoring and diagnosis of the simulated injector fault due to the small effect of the simulated fault on the engine combustion process. Nevertheless, good correlations between the simulated injector fault and the lower order components of the enveloped in-cylinder pressure spectrum were found at various engine loading conditions.

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The availability of bridges is crucial to people’s daily life and national economy. Bridge health prediction plays an important role in bridge management because maintenance optimization is implemented based on prediction results of bridge deterioration. Conventional bridge deterioration models can be categorised into two groups, namely condition states models and structural reliability models. Optimal maintenance strategy should be carried out based on both condition states and structural reliability of a bridge. However, none of existing deterioration models considers both condition states and structural reliability. This study thus proposes a Dynamic Objective Oriented Bayesian Network (DOOBN) based method to overcome the limitations of the existing methods. This methodology has the ability to act upon as a flexible unifying tool, which can integrate a variety of approaches and information for better bridge deterioration prediction. Two demonstrative case studies are conducted to preliminarily justify the feasibility of the methodology

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Stimulated human whole saliva (WS) was used to study the dynamics of papain hydrolysis at defined pH, ionic strength and temperature with the view of reducing an acquired pellicle. A quartz crystal microbalance with dissipation (QCM-D) was used to monitor the changes in frequency due to enzyme hydrolysis of WS films and the hydrolytic parameters were calculated using an empirical model. The morphological and conformational changes of the salivary films before and after enzymatic hydrolysis were characterized by atomic force microscopy (AFM) imaging and grazing angle infrared spectroscopy (GA-FTIR) spectra, respectively. The characteristics of papain hydrolysis of WS films were pH-, ionic strength- and temperature-dependent. The WS films were partially removed by the action of enzyme, resulting thinner and smoother surfaces. The IR data suggested that hydrolysis-induced deformation did not occur onto the remnants salivary films. The processes of papain hydrolysis of WS films can be controlled by properly regulating pH, ionic strength and temperature.

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Existing recommendation systems often recommend products to users by capturing the item-to-item and user-to-user similarity measures. These types of recommendation systems become inefficient in people-to-people networks for people to people recommendation that require two way relationship. Also, existing recommendation methods use traditional two dimensional models to find inter relationships between alike users and items. It is not efficient enough to model the people-to-people network with two-dimensional models as the latent correlations between the people and their attributes are not utilized. In this paper, we propose a novel tensor decomposition-based recommendation method for recommending people-to-people based on users profiles and their interactions. The people-to-people network data is multi-dimensional data which when modeled using vector based methods tend to result in information loss as they capture either the interactions or the attributes of the users but not both the information. This paper utilizes tensor models that have the ability to correlate and find latent relationships between similar users based on both information, user interactions and user attributes, in order to generate recommendations. Empirical analysis is conducted on a real-life online dating dataset. As demonstrated in results, the use of tensor modeling and decomposition has enabled the identification of latent correlations between people based on their attributes and interactions in the network and quality recommendations have been derived using the 'alike' users concept.

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Online social networks can be found everywhere from chatting websites like MSN, blogs such as MySpace to social media such as YouTube and second life. Among them, there is one interesting type of online social networks, online dating network that is growing fast. This paper analyzes an online dating network from social network analysis point of view. Observations are made and results are obtained in order to suggest a better recommendation system for people-to-people networks.

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A new relationship type of social networks - online dating - are gaining popularity. With a large member base, users of a dating network are overloaded with choices about their ideal partners. Recommendation methods can be utilized to overcome this problem. However, traditional recommendation methods do not work effectively for online dating networks where the dataset is sparse and large, and a two-way matching is required. This paper applies social networking concepts to solve the problem of developing a recommendation method for online dating networks. We propose a method by using clustering, SimRank and adapted SimRank algorithms to recommend matching candidates. Empirical results show that the proposed method can achieve nearly double the performance of the traditional collaborative filtering and common neighbor methods of recommendation.

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Humans have altered environments and enhanced their well being unlike any other creature on the planet (Heilman & Donna, 2007); this is no different whether the environment is ecological, social or organisational. In recent times business modelling techniques have become intricately detailed in the pre-designing and evaluating of business flow before the final implementation (Ou-Yang & Lin, 2008). The importance of the organisation change and business process model is undeniable. The feedback received from real business process users is that the notation is easy to learn; the models do help people to understand the process better; the models can be used to improve the (business) process; and the notation is expressive enough to capture the essential information (Bennett, Doshi, Do Vale Junior, Kumar, Manikam, & Madavan, 2009).

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Precise protein quantification is essential in clinical dietetics, particularly in the management of renal, burn and malnourished patients. The EP-10 was developed to expedite the estimation of dietary protein for nutritional assessment and recommendation. The main objective of this study was to compare the validity and efficacy of the EP-10 with the American Dietetic Association’s “Exchange List for Meal Planning” (ADA-7g) in quantifying dietary protein intake, against computerised nutrient analysis (CNA). Protein intake of 197 food records kept by healthy adult subjects in Singapore was determined thrice using three different methods – (1) EP-10, (2) ADA-7g and (3) CNA using SERVE program (Version 4.0). Assessments using the EP-10 and ADA-7g were performed by two assessors in a blind crossover manner while a third assessor performed the CNA. All assessors were blind to each other’s results. Time taken to assess a subsample (n=165) using the EP-10 and ADA-7g was also recorded. Mean difference in protein intake quantification when compared to the CNA was statistically non-significant for the EP-10 (1.4 ± 16.3 g, P = .239) and statistically significant for the ADA-7g (-2.2 ± 15.6 g, P = .046). Both the EP-10 and ADA-7g had clinically acceptable agreement with the CNA as determined via Bland-Altman plots, although it was found that EP-10 had a tendency to overestimate with protein intakes above 150 g. The EP-10 required significantly less time for protein intake quantification than the ADA-7g (mean time of 65 ± 36 seconds vs. 111 ± 40 seconds, P < .001). The EP-10 and ADA-7g are valid clinical tools for protein intake quantification in an Asian context, with EP-10 being more time efficient. However, a dietician’s discretion is needed when the EP-10 is used on protein intakes above 150g.

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Collaborative question answering (cQA) portals such as Yahoo! Answers allow users as askers or answer authors to communicate, and exchange information through the asking and answering of questions in the network. In their current set-up, answers to a question are arranged in chronological order. For effective information retrieval, it will be advantageous to have the users’ answers ranked according to their quality. This paper proposes a novel approach of evaluating and ranking the users’answers and recommending the top-n quality answers to information seekers. The proposed approach is based on a user-reputation method which assigns a score to an answer reflecting its answer author’s reputation level in the network. The proposed approach is evaluated on a dataset collected from a live cQA, namely, Yahoo! Answers. To compare the results obtained by the non-content-based user-reputation method, experiments were also conducted with several content-based methods that assign a score to an answer reflecting its content quality. Various combinations of non-content and content-based scores were also used in comparing results. Empirical analysis shows that the proposed method is able to rank the users’ answers and recommend the top-n answers with good accuracy. Results of the proposed method outperform the content-based methods, various combinations, and the results obtained by the popular link analysis method, HITS.

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This paper reports on a six month longitudinal study exploring people’s emotional experience with two categories of portable interactive devices (PIDs); media and health related PIDs. The focus is on emotions and how PIDs mediate these experiences in everyday contexts. Previous findings presented by the authors (Gomez 2009, 2010) revealed that people’s emotional experiences with PIDs over time are influenced by whether interactions were at a personal or social level. This paper presents four categories of activities identified and their relationship to emotional experiences with PIDs that have been developed through further analysis of the data. It concludes with a discussion of the findings and their implications to the field of Design on the design of future PIDs.

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A novel m-ary tree based approach is presented to solve asset management decisions which are combinatorial in nature. The approach introduces a new dynamic constraint based control mechanism which is capable of excluding infeasible solutions from the solution space. The approach also provides a solution to the challenges with ordering of assets decisions.