A Training Sample Sequence Planning Method for Pattern Recognition Problems

In solving pattern recognition problems, many classification methods, such as the nearest-neighbor (NN) rule, need to determine prototypes from a training set. To improve the performance of these classifiers in finding an efficient set of prototypes, this paper introduces a training sample sequence planning method. In particular, by estimating the relative nearness of the training samples to the decision boundary, the approach proposed here incrementally increases the number of prototypes until the desired classification accuracy has been reached. This approach has been tested with a NN classification method and a neural network training approach. Studies based on both artificial and real data demonstrate that higher classification accuracy can be achieved with fewer prototypes

The integration of rapid prototyping within industrial design practice

Three-dimensional appearance models represent an essential outcome of industrial design practice, facilitating the origination, evaluation and specification of exterior form. As manufacturers face increasing pressure to reduce time scales for new product development, the production of such models using conventional fabrication techniques must be appraised. As a means of economically translating digital geometry into one-off components, rapid prototyping has the potential to contribute towards a reduction in lead times for the production of appearance models. The objective of this research is to propose a methodological approach for the effective integration of rapid prototyping within industrial design practice. The field and practice of industrial design is defined, the technology of rapid prototyping discussed, and their integration proposed through a draft computer-aided industrial design/rapid prototyping (CAID/RP) methodological approach. This is exposed to practitioner feedback, modified, and employed as a revised CAID/RP methodological approach during the industrial design of a nylon line trimmer. The product outcome is used to compare and contrast the production of an appearance model via rapid prototyping, an appearance prototype via rapid prototyping, and an appearance model via conventional fabrication techniques. Two issues arise from the use of the revised CAID/RP methodological approach: the production of stl files and the lack of physical interaction with product form. In addition, the emergence of rapid prototype sketch modelling systems following the line trimmer case study provides an opportunity for further enhancement. A strategy for the resolution of these issues is proposed, and their effectiveness evaluated through additional case studies. The resulting CAID/RP methodological approach is subject to validation through practitioner interviews and a normalised rating/weighting method. The positive feedback acknowledges the significance of the CAID/RP methodological approach through a reduction in product development lead times and enhancement of professional practice. The project makes a contribution to new knowledge and understanding in the area of professional practice through the definition and validation of operational paradigmatic change

Haptic Hybrid Prototyping (HHP): An AR Application for Texture Evaluation with Semantic Content in Product Design

The manufacture of prototypes is costly in economic and temporal terms and in order to carry this out it is necessary to accept certain deviations with respect to the final finishes. This article proposes haptic hybrid prototyping, a haptic-visual product prototyping method created to help product design teams evaluate and select semantic information conveyed between product and user through texturing and ribs of a product in early stages of conceptualization. For the evaluation of this tool, an experiment was realized in which the haptic experience was compared during the interaction with final products and through the HHP. As a result, it was observed that the answers of the interviewees coincided in both situations in 81% of the cases. It was concluded that the HHP enables us to know the semantic information transmitted through haptic-visual means between product and user as well as being able to quantify the clarity with which this information is transmitted. Therefore, this new tool makes it possible to reduce the manufacturing lead time of prototypes as well as the conceptualization phase of the product, providing information on the future success of the product in the market and its economic return

Choice architecture and design with intent

Motivation – Choice architecture (Thaler & Sunstein, 2008) is a phrase of the moment among politicians and economists seeking to influence public behaviour, but the relevance of the concept to designers has received little attention. This paper places choice architecture within the context of Design with Intent—design intended to influence user behaviour. Research approach – The concepts are introduced and choice architecture is deconstructed. Findings/Design – Affordances and Simon’s behavioural model (1955) help understand choice architecture in more detail. Research limitations/Implications – This is only a very brief, limited foray into what choice architecture is. Originality/Value – User behaviour can be a major determinant of product efficiency: user decisions can contribute significantly to environmental impacts. Understanding the reasons behind them, a range of design techniques can be identified to help users towards more efficient interactions. Take away message – The intended outcome is a useful design method for helping users use things more efficiently

Forgetting Exceptions is Harmful in Language Learning

We show that in language learning, contrary to received wisdom, keeping exceptional training instances in memory can be beneficial for generalization accuracy. We investigate this phenomenon empirically on a selection of benchmark natural language processing tasks: grapheme-to-phoneme conversion, part-of-speech tagging, prepositional-phrase attachment, and base noun phrase chunking. In a first series of experiments we combine memory-based learning with training set editing techniques, in which instances are edited based on their typicality and class prediction strength. Results show that editing exceptional instances (with low typicality or low class prediction strength) tends to harm generalization accuracy. In a second series of experiments we compare memory-based learning and decision-tree learning methods on the same selection of tasks, and find that decision-tree learning often performs worse than memory-based learning. Moreover, the decrease in performance can be linked to the degree of abstraction from exceptions (i.e., pruning or eagerness). We provide explanations for both results in terms of the properties of the natural language processing tasks and the learning algorithms.Comment: 31 pages, 7 figures, 10 tables. uses 11pt, fullname, a4wide tex styles. Pre-print version of article to appear in Machine Learning 11:1-3, Special Issue on Natural Language Learning. Figures on page 22 slightly compressed to avoid page overloa

Multidimensional Pareto optimization of touchscreen keyboards for speed, familiarity and improved spell checking

The paper presents a new optimization technique for keyboard layouts based on Pareto front optimization. We used this multifactorial technique to create two new touchscreen phone keyboard layouts based on three design metrics: minimizing finger travel distance in order to maximize text entry speed, a new metric to maximize the quality of spell correction quality by minimizing neighbouring key ambiguity, and maximizing familiarity through a similarity function with the standard Qwerty layout. The paper describes the optimization process and resulting layouts for a standard trapezoid shaped keyboard and a more rectangular layout. Fitts' law modelling shows a predicted 11% improvement in entry speed without taking into account the significantly improved error correction potential and the subsequent effect on speed. In initial user tests typing speed dropped from approx. 21wpm with Qwerty to 13wpm (64%) on first use of our layout but recovered to 18wpm (85%) within four short trial sessions, and was still improving. NASA TLX forms showed no significant difference on load between Qwerty and our new layout use in the fourth session. Together we believe this shows the new layouts are faster and can be quickly adopted by users

Co-design of sectoral climate services based on seasonal prediction information in the Mediterranean

We present in this contribution the varied experiences gathered in the co-design of a sectoral climate services collection, developed in the framework of the MEDSCOPE project, which have in common the application of seasonal predictions for the Mediterranean geographical and climatic region. Although the region is affected by low seasonal predictability limiting the skill of seasonal forecasting systems, which historically has hindered the development of downstream services, the project was originally conceived to exploit windows of opportunity with enhanced skill for developing and evaluating climate services in various sectors with high societal impact in the region: renewable energy, hydrology, and agriculture and forestry. The project also served as the scientific branch of the WMO-led Mediterranean Climate Outlook Forum (MedCOF) that had as objective -among others- partnership strengthening on climate services between providers and users within the Mediterranean region. The diversity of the MEDSCOPE experiences in co-designing shows the wide range of involvement and engagement of users in this process across the Mediterranean region, which benefits from the existing solid and organized MedCOF community of climate services providers and users. A common issue among the services described here -and also among other prototypes developed in the project- was related with the communication of forecasts uncertainty and skill for efficiently informing decision-making in practice. All MEDSCOPE project prototypes make use of an internally developed software package containing process-based methods for synthesising seasonal forecast data, as well as basic and advanced tools for obtaining tailored products. Another challenge assumed by the project refers to the demonstration of the economic, social, and environmental value of predictions provided by these MEDSCOPE prototypes.The work described in this paper has received funding from the MEDSCOPE project co-funded by the European Commission as part of ERA4CS, an ERA-NET initiated by JPI Climate, grant agreement 690462

Co-design of sectoral climate services based on seasonal prediction information in the Mediterranean

We present in this contribution the varied experiences gathered in the co-design of a sectoral climate services collection, developed in the framework of the MEDSCOPE project, which have in common the application of seasonal predictions for the Mediterranean geographical and climatic region. Although the region is affected by low seasonal predictability limiting the skill of seasonal forecasting systems, which historically has hindered the development of downstream services, the project was originally conceived to exploit windows of opportunity with enhanced skill for developing and evaluating climate services in various sectors with high societal impact in the region: renewable energy, hydrology, and agriculture and forestry. The project also served as the scientific branch of the WMO-led Mediterranean Climate Outlook Forum (MedCOF) that had as objective -among others- partnership strengthening on climate services between providers and users within the Mediterranean region. The diversity of the MEDSCOPE experiences in co-designing shows the wide range of involvement and engagement of users in this process across the Mediterranean region, which benefits from the existing solid and organized MedCOF community of climate services providers and users. A common issue among the services described here -and also among other prototypes developed in the project- was related with the communication of forecasts uncertainty and skill for efficiently informing decision-making in practice. All MEDSCOPE project prototypes make use of an internally developed software package containing process-based methods for synthesising seasonal forecast data, as well as basic and advanced tools for obtaining tailored products. Another challenge assumed by the project refers to the demonstration of the economic, social, and environmental value of predictions provided by these MEDSCOPE prototypes.The work described in this paper has received funding from the MEDSCOPE project co-funded by the European Commission as part of ERA4CS, an ERA-NET initiated by JPI Climate, grant agreement 690462.Peer Reviewed"Article signat per 16 autors/es: Eroteida Sánchez-García, Ernesto Rodríguez-Camino, Valentina Bacciu, Marta Chiarle, José Costa-Saura, Maria Nieves Garrido, Llorenç Lledó, Beatriz Navascués, Roberta Paranunzio, Silvia Terzag, Giulio Bongiovanni, Valentina Mereu, Guido Nigrelli, Monia Santini, Albert Soret, Jostvon Hardenberg"Postprint (published version