Training Bayesian networks for image segmentation

We are concerned with the problem of image segmentation in which each pixel is assigned to one of a predefined finite number of classes. In Bayesian image analysis, this requires fusing together local predictions for the class labels with a prior model of segmentations. Markov Random Fields (MRFs) have been used to incorporate some of this prior knowledge, but this not entirely satisfactory as inference in MRFs is NP-hard. The multiscale quadtree model of Bouman and Shapiro (1994) is an attractive alternative, as this is a tree-structured belief network in which inference can be carried out in linear time (Pearl 1988). It is an hierarchical model where the bottom-level nodes are pixels, and higher levels correspond to downsampled versions of the image. The conditional-probability tables (CPTs) in the belief network encode the knowledge of how the levels interact. In this paper we discuss two methods of learning the CPTs given training data, using (a) maximum likelihood and the EM algorithm and (b) emphconditional maximum likelihood (CML). Segmentations obtained using networks trained by CML show a statistically-significant improvement in performance on synthetic images. We also demonstrate the methods on a real-world outdoor-scene segmentation task

Izraženost surfaktantnog proteina B u bronhoalveolarnom ispirku terminske novorođenčadi sa sindromom respiracijskog distresa

The aim was to investigate the surfactant protein B (SP-B) expression in the bronchoalveolar lavage fluid (BALF ) of full-term neonates with respiratory distress syndrome (RD S). The enzyme-linked immunosorbent assay was performed to assess SP-B expression in BALF of 60 full-term neonates with RD S and 23 healthy neonates and correlation of SP-B level with RD S classification according to chest x-ray findings and PaO2/FiO2 before mechanical ventilation in neonates with RD S. The SP-B level was significantly lower in the RD S group (17.63±6.80 ng/mL) than in healthy neonates (103.95±6.38 ng/mL) (P<0.001). The SP-B level correlated positively with PaO2/ FiO2 before mechanical ventilation (r=0.838, P<0.001). Moreover, the lower the SP-B level, the more severe was the RD S as determined by chest x-ray (P<0.001). In conclusion, full-term neonates with RD S had reduced SP-B in BALF , which was related to the severity of RD S, suggesting that SP-B supplement may be an effective strategy in the treatment of RD S in full-term neonates.Cilj studije bio je ispitati izraženost surfaktantnog proteina B (SP-B) u bronhoalveolarnom ispirku (BALF ) terminske novorođenčadi sa sindromom respiracijskog distresa (SRD ). Izraženost SP-B određena je testom ELI SA u BALF 60 terminske novorođenčadi sa SRD i 23 zdrave novorođenčadi. Utvrđena je korelacija razine SP-B s klasifikacijom SRD prema rendgenskoj snimci prsišta i vrijednosti PaO2/FiO2 prije mehaničke ventilacije u novorođenčadi sa SRD . U skupini novorođenčadi sa SRD razina SP-B bila je značajno niža (17,63±6,80 ng/mL) od one u zdrave novorođenčadi (103,95±6,38 ng/ mL) (P<0,001). Utvrđena je pozitivna korelacija razine SP-B i PaO2/FiO2 prije mehaničke ventilacije (r=0,838, P<0,001). Štoviše, što je bila niža razina SP-B, to je teži bio SRD procijenjen prema rendgenskoj snimci prsišta (P<0,001). Zaključuje se da terminska novorođenčad sa SRD ima sniženu razinu SP-B u BALF i to je povezano s težinom SRD . Ovi nalazi ukazuju na to da bi dodatak SP-B mogla biti učinkovita strategija u liječenju SRD kod terminske novorođenčadi

Fault Attack on the Authenticated Cipher ACORN v2

Fault attack is an efficient cryptanalysis method against cipher implementations and has attracted a lot of attention in recent public cryptographic literatures. In this work we introduce a fault attack on the CAESAR candidate ACORN v2. Our attack is done under the assumption of random fault injection into an initial state of ACORN v2 and contains two main steps: fault locating and equation solving. At the first step, we first present a fundamental fault locating method, which uses 99-bit output keystream to determine the fault injected location with probability 97.08%. And then several improvements are provided, which can further increase the probability of fault locating to almost 1. As for the system of equations retrieved at the first step, we give two solving methods at the second step, that is, linearization and guess-and-determine. The time complexity of our attack is not larger than c·2179.19-1.76N at worst, where N is the number of fault injections such that 31≤N≤88 and c is the time complexity of solving linear equations. Our attack provides some insights into the diffusion ability of such compact stream ciphers

Fault Attack on ACORN v3

Fault attack is one of the most efficient side channel attacks and has attracted much attention in recent public cryptographic literatures. In this work we introduce a fault attack on the authenticated cipher ACORN v3. Our attack is done under the assumption that a fault is injected into an initial state of ACORN v3 randomly, and contains two main steps: fault locating and equation solving. At the first step, we introduce concepts of unique set and non-unique set, where differential strings belonging to unique sets can determine the fault location uniquely. For strings belonging to non-unique sets, we use some strategies to increase the probability of determining the fault location uniquely to almost 1. At the second step, we demonstrate several ways of retrieving equations, and then obtain the initial state by solving equations with the guess-and-determine method. With $n$ fault experiments, we can recover the initial state with time complexity $c \cdot2^{146.5-3.52\cdot n}$, where $c$ is the time complexity of solving linear equations and $26<n<43$. We also apply the attack to ACORN v2, which shows that, comparing with ACORN v2, the tweaked version ACORN v3 is more vulnerable against the fault attack

The role of earthquakes and storms in the fluvial export of terrestrial organic carbon along the eastern margin of the Tibetan plateau: A biomarker perspective

Driven by earthquakes and intense rainfall, steep tectonically active mountains are hotspots of terrestrial organic carbon mobilization from soils, rocks, and vegetation by landslides into rivers. Subsequent delivery and fluvial mobilization of organic carbon from different sources can impact atmospheric CO2 concentrations across a range of timescales. Extreme landslide triggering events can provide insight on processes and rates of carbon export. Here we used suspended sediment collected from 2005 to 2012 at the upper Min Jiang, a main tributary of the Yangtze River on the eastern margin of the Tibetan Plateau, to compare the erosion of terrestrial organic carbon before and after the 2008 Wenchuan earthquake and a storm-derived debris flow event in 2005. To constrain the source of riverine particulate organic carbon (POC), we quantified lignin phenols and n-alkanoic acids in the suspended sediments, catchment soils and landslide deposits. We found that riverine POC had higher inputs of less-degraded, discrete organic matter at high suspended sediment loads, while the source of POC seemed stochastic at low suspended sediment concentrations. The debris flow in 2005 mobilized a large amount of POC, resulting in an export of lignin within a single day equivalent to a normal year. In comparison, the 2008 Wenchuan earthquake increased the flux of POC and particulate lignin, albeit with limited impact on POC sources in comparison to seasonal variations. Our results highlight the important role of episodic events in the fluvial export of terrestrial carbon