Voxel selection in fMRI data analysis based on sparse representation

Multivariate pattern analysis approaches toward detection of brain regions from fMRI data have been gaining attention recently. In this study, we introduce an iterative sparse-representation-based algorithm for detection of voxels in functional MRI (fMRI) data with task relevant information. In each iteration of the algorithm, a linear programming problem is solved and a sparse weight vector is subsequently obtained. The final weight vector is the mean of those obtained in all iterations. The characteristics of our algorithm are as follows: 1) the weight vector (output) is sparse; 2) the magnitude of each entry of the weight vector represents the significance of its corresponding variable or feature in a classification or regression problem; and 3) due to the convergence of this algorithm, a stable weight vector is obtained. To demonstrate the validity of our algorithm and illustrate its application, we apply the algorithm to the Pittsburgh Brain Activity Interpretation Competition 2007 functional fMRI dataset for selecting the voxels, which are the most relevant to the tasks of the subjects. Based on this dataset, the aforementioned characteristics of our algorithm are analyzed, and a comparison between our method with the univariate general-linear-model-based statistical parametric mapping is performed. Using our method, a combination of voxels are selected based on the principle of effective/sparse representation of a task. Data analysis results in this paper show that this combination of voxels is suitable for decoding tasks and demonstrate the effectiveness of our method

SusOrganic - Development of quality standards and optimised processing methods for organic produce - Final report

The SusOrganic project aimed to develop improved drying and cooling/freezing processes for organic products in terms of sustainability and objective product quality criteria. Initially, the consortium focused on a predefined set products to investigate (fish, meat, fruits and vegetables). Contacting participants in the fruit and vegetable sector showed that there is only little perceived need for making changes for the improvement of the processes. At the same time, it became clear that hops and herb producers (drying) face several challenges in terms of product quality and cost of drying processes. Therefore, the range of products was extended to these products. The results of a consumer survey conducted as part the project showed clearly that consumers trust in the organic label, but also tend to mix up the term organic with regional or fair ­trade. Further, the primary production on farm and not the processing is explicitly included in the consumers’ evaluation of sustainability. Appearance of organic products was found to be one of the least important quality criteria or attributes regarding buying decisions. However, there are indications that an imperfect appearance could be a quality attribute for consumers, as the product then is perceived to be processed without artificial additives. Regarding drying operations, small scale producers in the organic sector often work with old and/or modified techniques and technologies, which often leads to an inefficient drying processes due to high energy consumptions and decreased product quality. Inappropriate air volume flow and distribution often cause inefficient removal of the moisture from the product and heterogeneous drying throughout the bulk. Guidelines for improvement of the physical setup of existing driers as well as designs for new drying operations, including novel drying strategies were developed. Besides chilling and freezing, the innovative idea of superchilling was included into the project.The superchilled cold chain is only a few degrees colder than the refrigeration chain but has a significant impact on the preservation characteristic due to shock frosting of the outer layer of the product and the further distribution of very small ice crystals throughout the product during storage. Super­chilling of organically grown salmon eliminated the demand of ice for transport, resulting in both, a reduction of energy costs and a better value chain performance in terms of carbon foot printing. This is mainly due to the significantly reduced transport volume and weight without the presence of ice. The product quality is not different but the shelf life is extended compared to chilled fish. This means that the high quality of organic salmon can be maintained over a longer time period, which can be helpful,e.g. to reach far distant markets. The same trend was found for superchilled organic meat products such as pork and chicken. The consortium also developed innovative noninvasive measurement and control systems and improved drying strategies and systems for fruits, vegetables, herbs, hops and meat. Those systems are based on changes occurring inside the product and therefore require observation strategies of the product during the drying process. Through auditing campaigns as well as pilot scale drying tests it has been possible to develop optimisation strategies for both herb and hops commodities, which can help reduce microbial spoilage and retain higher levels of volatile product components whilst reducing the energy demands. These results can be applied with modifications to the other commodities under investigation. The environmental and cost performance of superchilling of salmon and drying of meat, fruit and vegetables were also investigated and the findings indicated that both superchilling and drying could improve sustainability of organic food value chains especially in case of far distant markets. An additional outcome of the project, beyond the original scope was the development of a noninvasive, visual sensor based detection system for authenticity checks of meat products in terms of fresh and prefrozen meats

Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes

I argue that data becomes temporarily interesting by itself to some self-improving, but computationally limited, subjective observer once he learns to predict or compress the data in a better way, thus making it subjectively simpler and more beautiful. Curiosity is the desire to create or discover more non-random, non-arbitrary, regular data that is novel and surprising not in the traditional sense of Boltzmann and Shannon but in the sense that it allows for compression progress because its regularity was not yet known. This drive maximizes interestingness, the first derivative of subjective beauty or compressibility, that is, the steepness of the learning curve. It motivates exploring infants, pure mathematicians, composers, artists, dancers, comedians, yourself, and (since 1990) artificial systems.Comment: 35 pages, 3 figures, based on KES 2008 keynote and ALT 2007 / DS 2007 joint invited lectur

Automatically Discovering, Reporting and Reproducing Android Application Crashes

Mobile developers face unique challenges when detecting and reporting crashes in apps due to their prevailing GUI event-driven nature and additional sources of inputs (e.g., sensor readings). To support developers in these tasks, we introduce a novel, automated approach called CRASHSCOPE. This tool explores a given Android app using systematic input generation, according to several strategies informed by static and dynamic analyses, with the intrinsic goal of triggering crashes. When a crash is detected, CRASHSCOPE generates an augmented crash report containing screenshots, detailed crash reproduction steps, the captured exception stack trace, and a fully replayable script that automatically reproduces the crash on a target device(s). We evaluated CRASHSCOPE's effectiveness in discovering crashes as compared to five state-of-the-art Android input generation tools on 61 applications. The results demonstrate that CRASHSCOPE performs about as well as current tools for detecting crashes and provides more detailed fault information. Additionally, in a study analyzing eight real-world Android app crashes, we found that CRASHSCOPE's reports are easily readable and allow for reliable reproduction of crashes by presenting more explicit information than human written reports.Comment: 12 pages, in Proceedings of 9th IEEE International Conference on Software Testing, Verification and Validation (ICST'16), Chicago, IL, April 10-15, 2016, pp. 33-4

Test, Reliability and Functional Safety Trends for Automotive System-on-Chip

This paper encompasses three contributions by industry professionals and university researchers. The contributions describe different trends in automotive products, including both manufacturing test and run-time reliability strategies. The subjects considered in this session deal with critical factors, from optimizing the final test before shipment to market to in-field reliability during operative life