7,648 research outputs found

    Temperature 1 Self-Assembly: Deterministic Assembly in 3D and Probabilistic Assembly in 2D

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    We investigate the power of the Wang tile self-assembly model at temperature 1, a threshold value that permits attachment between any two tiles that share even a single bond. When restricted to deterministic assembly in the plane, no temperature 1 assembly system has been shown to build a shape with a tile complexity smaller than the diameter of the shape. In contrast, we show that temperature 1 self-assembly in 3 dimensions, even when growth is restricted to at most 1 step into the third dimension, is capable of simulating a large class of temperature 2 systems, in turn permitting the simulation of arbitrary Turing machines and the assembly of n×nn\times n squares in near optimal O(logn)O(\log n) tile complexity. Further, we consider temperature 1 probabilistic assembly in 2D, and show that with a logarithmic scale up of tile complexity and shape scale, the same general class of temperature τ=2\tau=2 systems can be simulated with high probability, yielding Turing machine simulation and O(log2n)O(\log^2 n) assembly of n×nn\times n squares with high probability. Our results show a sharp contrast in achievable tile complexity at temperature 1 if either growth into the third dimension or a small probability of error are permitted. Motivated by applications in nanotechnology and molecular computing, and the plausibility of implementing 3 dimensional self-assembly systems, our techniques may provide the needed power of temperature 2 systems, while at the same time avoiding the experimental challenges faced by those systems

    Postmortem iris recognition and its application in human identification

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    Iris recognition is a validated and non-invasive human identification technology currently implemented for the purposes of surveillance and security (i.e. border control, schools, military). Similar to deoxyribonucleic acid (DNA), irises are a highly individualizing component of the human body. Based on a lack of genetic penetrance, irises are unique between an individual’s left and right iris and between identical twins, proving to be more individualizing than DNA. At this time, little to no research has been conducted on the use of postmortem iris scanning as a biometric measurement of identification. The purpose of this pilot study is to explore the use of iris recognition as a tool for postmortem identification. Objectives of the study include determining whether current iris recognition technology can locate and detect iris codes in postmortem globes, and if iris scans collected at different postmortem time intervals can be identified as the same iris initially enrolled. Data from 43 decedents involving 148 subsequent iris scans demonstrated a subsequent match rate of approximately 80%, supporting the theory that iris recognition technology is capable of detecting and identifying an individual’s iris code in a postmortem setting. A chi-square test of independence showed no significant difference between match outcomes and the globe scanned (left vs. right), and gender had no bearing on the match outcome. There was a significant relationship between iris color and match outcome, with blue/gray eyes yielding a lower match rate (59%) compared to brown (82%) or green/hazel eyes (88%), however, the sample size of blue/gray eyes in this study was not large enough to draw a meaningful conclusion. An isolated case involving an antemortem initial scan collected from an individual on life support yielded an accurate identification (match) with a subsequent scan captured at approximately 10 hours postmortem. Falsely rejected subsequent iris scans or "no match" results occurred in about 20% of scans; they were observed at each PMI range and varied from 19-30%. The false reject rate is too high to reliably establish non-identity when used alone and ideally would be significantly lower prior to implementation in a forensic setting; however, a "no match" could be confirmed using another method. Importantly, the data showed a false match rate or false accept rate (FAR) of zero, a result consistent with previous iris recognition studies in living individuals. The preliminary results of this pilot study demonstrate a plausible role for iris recognition in postmortem human identification. Implementation of a universal iris recognition database would benefit the medicolegal death investigation and forensic pathology communities, and has potential applications to other situations such as missing persons and human trafficking cases

    Ars Informatica -- Ars Electronica: Improving Sonification Aesthetics

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    In this paper we discuss æsthetic issues of sonifications. We posit that many sonifications have suffered from poor acoustic ecology which makes listening more difficult, thereby resulting in poorer data extraction and inference on the part of the listener. Lessons are drawn from the electro acoustic music community as we argue that it is not instructive to distinguish between sonifications and music/sound art. Edgar Var`ese defined music as organised sound and sonifications organise sound to reflect some aspect of the thing being sonified. Therefore, we propose that sonification designers can improve the communicative ability of their auditory displays by paying attention to the æsthetic issues that are well known to composers, orchestrators, sound designers & artists, and recording engineers

    On the Tradeoff between Speedup and Energy Consumption in High Performance Computing – A Bioinformatics Case Study

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    High Performance Computing has been very useful to researchers in the Bioinformatics, Medical and related fields. The bioinformatics domain is rich in applications that require extracting useful information from very large and continuously growing sequence of databases. Automated techniques such as DNA sequencers, DNA microarrays & others are continually growing the dataset that is stored in large public databases such as GenBank and Protein DataBank. Most methods used for analyzing genetic/protein data have been found to be extremely computationally intensive, providing motivation for the use of powerful computers or systems with high throughput characteristics. In this paper, we provide a case study for one such bioinformatics application called BLAT running in a high performance computing environment. We use sequences gathered from researchers and parallelize the runs to study the performance characteristics under three different query and data partitioning models. This research highlights the need to carefully develop a parallel model with energy awareness in mind, based on our understanding of the application and then appropriately designing a parallel model that works well for the specific application and domain. We found that the BLAT program is highly parallelizable and a high degree of speedup is achievable. The experiments suggest that the speed up depends on model used for query and database segmentation
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