Towards a parallel computationally efficient approach to scaling up data stream classification

Advances in hardware technologies allow to capture and process data in real-time and the resulting high throughput data streams require novel data mining approaches. The research area of Data Stream Mining (DSM) is developing data mining algorithms that allow us to analyse these continuous streams of data in real-time. The creation and real-time adaption of classification models from data streams is one of the most challenging DSM tasks. Current classifiers for streaming data address this problem by using incremental learning algorithms. However, even so these algorithms are fast, they are challenged by high velocity data streams, where data instances are incoming at a fast rate. This is problematic if the applications desire that there is no or only a very little delay between changes in the patterns of the stream and absorption of these patterns by the classifier. Problems of scalability to Big Data of traditional data mining algorithms for static (non streaming) datasets have been addressed through the development of parallel classifiers. However, there is very little work on the parallelisation of data stream classification techniques. In this paper we investigate K-Nearest Neighbours (KNN) as the basis for a real-time adaptive and parallel methodology for scalable data stream classification tasks.

Narratives of grassroots innovations: a comparison of voluntary simplicity and the transition movement in Italy

Grassroots innovations (GI) are promising examples of deliberate transformation of socio-technical systems towards resilience and sustainability. However, evidence is needed on the factors that limit or enable their success. This paper set out to study how GI use narratives to empower innovation in the face of incumbent socio-technical regimes. Institutional documents were comparatively analyzed to assess how the narratives influence the structure, form of action and external interactions of two Italian grassroots networks, Bilanci di Giustizia and Transition Network Italy. The paper finds an internal consistency between narratives and strategies for each of the two networks. The paper also highlights core similarities, but also significant differences in the ethical basis of the two narratives, and in the organizations and strategies. Such differences determine different forms of innovation empowerment and expose the niche to different potentials to transform incumbent regimes, or to the risk of being co-opted by them.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

Segmenting the Italian coffee market: marketing opportunities for economic agents working along the international coffee chain

Globalization, either directly or indirectly (e.g. through structural adjustment reforms), has called for profound changes in the previously existing institutional order. Some changes adversely impacted the production and market environment of many coffee producers in developing countries resulting in more risky and less remunerative coffee transactions. This paper focuses on customization of a tropical commodity, fair-trade coffee, as an approach to mitigating the effects of worsened market conditions for small-scale coffee producers in less developed countries. fair-trade labeling is viewed as a form of “de-commodification” of coffee through product differentiation on ethical grounds. This is significant not only as a solution to the market failure caused by pervasive information asymmetries along the supply chain, but also as a means of revitalizing the agricultural-commodity-based trade of less developed countries (LDCs) that has been languishing under globalization. More specifically, fair-trade is an example of how the same strategy adopted by developed countries’ producers/ processors (i.e. the sequence product differentiation - institutional certification - advertisement) can be used by LDC producers to increase the reputation content of their outputs by transforming them from mere commodities into “decommodified” (i.e. customized and more reputed) goods. The resulting segmentation of the world coffee market makes possible to meet the demand by consumers with preference for this “(ethically) customized” coffee and to transfer a share of the accruing economic rents backward to the Fair-trade coffee producers in LDCs. It should however be stressed that this outcome cannot be taken for granted since investments are needed to promote the required institutional innovations. In Italy FTC is a niche market with very few private brands selling this product. However, an increase of FTC market share could be a big commercial opportunity for farmers in LDCs and other economic agents involved along the international coffee chain. Hence, this research explores consumers’ knowledge of labels promoting quality products, consumption coffee habits, brand loyalty, willingness to pay and market segmentation according to the heterogeneity of preferences for coffee products. The latter was assessed developing a D-efficient design where stimuli refinement was tested during two focus groups.

Do consumers want public or private bodies to monitor animal friendly production and marketing schemes? And does trust matter?

Producing according to enhanced farm animal welfare (FAW) standards increases costs along the livestock value chain, especially for monitoring certified animal friendly products. In the choice between public or private bodies for carrying out and monitoring certification, consumer preferences and trust play a role. We explore this issue by applying logit analysis involving socio-economic and psychometric variables to survey data from Italy. Results identify marked consumer preferences for public bodies and trust in stakeholders a key determinant.

A critical account of the relationship between institutional trust, risk perception, and technology acceptance with an application to genetically modified foods

This article critically reflects on the widely held view of a causal chain with trust in public authorities impacting technology acceptance via perceived risk. It first puts forward conceptual reason against this view, as the presence of risk is a precondition for trust playing a role in decision making. Second, results from consumer surveys in Italy and Germany are presented that support the associationist model as counter hypothesis. In that view, trust and risk judgments are driven by and thus simply indicators of higher order attitudes toward a certain technology which determine acceptance instead. The implications of these findings are discussed.

Trust in authorities monitoring the distribution of genetically modified foods: dimensionality, measurement issues, and determinants

Based on a combined internet and mail survey in Germany the independence of indica-tors of trust in public authorities from indicators of attitudes toward genetically modified food is tested. Despite evidence of a link between trust indicators on the one hand and evaluation of benefits and perceived likelihoods of risks, correlation with other factors is found to be moderate on average. But the trust indicators exhibit only a moderate relation with the re-spondents’ preference for either sole public control or a cooperation of public and private bodies in the monitoring of GM food distribution. Instead, age and location in either the New or the Old Lander are found to be significantly related with such preferences.

Electronic commerce in agriculture and agribusiness: the case of Emilia-Romagna (Italy )

Despite the expectations of the benefits of this tool, the adoption of Electronic Commerce (EC) by small and medium firms of the agro-food sector in Italy is still not frequent, however, the understanding of opportunities it could create and how they can be exploited remains a relevant issue. This study, carried out in the Emilia -Romagna region during 2002, illustrates the results of a survey of 208 firms at all stages of the agro-food chain aimed at understanding the use of the Internet and the strategies adopted for EC implementation. The results show a low level of implementation of the instrument and a limited variety of adoption strategies. Agro-food firms actually invest very little in EC focusing their efforts on the Internet as promotion tool, while web-based direct selling is confined to market niches. The view that the Internet would reverse the disadvantages of small firms appears by now non realistic, even if interesting opportunities for further development are still present.

GM food purchase intentions: linking the theory of planned behaviour with consumer trust and stated choice

After the “European” experience of BSE and further food safety crises consumer trust is playing an increasingly important role in political and marketing decision making. This also relates to the area of consumer acceptance of GM food. This paper integrates consumer trust with the theory of planned behavior and a stated choice model to gain a more complete picture of consumer decision making. Preliminary results indicate that when GM products offer practical benefits to consumers acceptance may increase considerably. Furthermore, both trust and perceived benefits contribute significantly to explaining the level of acceptance.

Consumer purchasing behaviour towards fish and seafood products: patterns and insights from a sample of international studies

The present systematic review was performed to assess consumer purchasing behaviour towards fish and seafood products in the wide context of developed countries. Web of Science, Scopus, ScienceDirect and Google Scholar engines were used to search the existing literature and a total of 49 studies were identified for inclusion. These studies investigated consumer purchasing behaviour towards a variety of fish and seafood products, in different countries and by means of different methodological approaches. In particular, the review identifies and discusses the main drivers and barriers of fish consumption as well as consumers’ preferences about the most relevant attributes of fish and seafood products providing useful insights for both practitioners and policy makers. Finally, main gaps of the existing literature and possible trajectories for future research are also discussed.

Benefits from safer animal food products: preliminary results from a contingent valuation study of Italian households

The social cost of food scares has been the object of substantial applied research worldwide. In Italy, meat and dairy products are often the vectors of food-borne pathogens, and this is well known by the public. Most cases of food contamination and poisoning find their causes in the way food is handled after, rather than before purchase. However, a large fraction is still caused by mishandling at the industrial stage. With this in mind, we set out to estimate Italian households’ willingness to pay (WTP) for a reduction in the risk of meat and dairy food contamination using contingent valuation. The survey design incorporated features specifically conceived to overcome difficulties faced in previous survey research, especially with respect to individualized food expenditures and risk communication. In order to achieve this objective a CAPI (computer-assisted personal interview) survey was devised to tackle two major issues which emerged in previous contingent valuation studies. The first issue is connected to the way of communicating risk to consumers in order to allow them to make optimal choices and the second one to the results deriving from these studies. In fact, estimates from contingent valuation regarding food safety are given just for single products and so marketers may find it hard to extrapolate them to the aggregate. Our results show that in Italy there are segments of consumers who would benefit from higher standards of food safety for farm animal products.

Prospettive economiche di mercato della produzione ortofrutticola biologica. Indagine sul gradimento dei consumatori

The aims of the present study are to explore the willingness to pay a tax for the abolition of the use of pesticides as well as a premium price per kilo for organically grown fruit. An investigation was carried out in the region of Emilia-Romagna both by means of face to face questionnaires administered randomly in large supermarkets and via the World Wide Web. The results of econometric estimates show that consumers in this region appear to be particularly sensitive to the ban of pesticides and willing to pay higher prices for such products.