Abnormal behavior detection using dominant sets

Smart surveillance systems are increasingly being used to detect potentially dangerous situations. To do so, the common and easier way is to model normal human behaviors and consider as abnormal any new strange behavior in the scene. In this article, Dominant Sets is adapted to model most frequent behaviors and to detect any unknown event to trigger an alarm. It is proved that after an unsupervised training, Dominant Sets can robustly detect abnormal behaviors. The method is tested in several different cases and compared to other usual clusterization methods such as KNN, mixture of Gaussians or Fuzzy \(K\) -Means to confirm its robustness and performance. The overall performance of abnormal behavior detection based on Dominant Sets is better, being the error ratio at least \(1.5\) points lower than the others.     

Good Enough is Good Enough: Overcoming Disaster Response Organizations’ Slow Social Media Data Adoption

Organizations that respond to disasters hold unreasonable standards for data arising from technology-enabled citizen contributions. This has strong negative potential for the ability of these responding organizations to incorporate these data into appropriate decision points. We argue that the landscape of the use of social media data in crisis response is varied, with pockets of use and acceptance among organizations. In this paper we present findings from interviews conducted with representatives from large international disaster response organizations concerning their use of social media data in crisis response. We found that emergency responders already operate with less than reliable, or “good enough,” information in offline practice, and that social media data are useful to responders, but only in specific crisis situations. Also, responders do use social media, but only within their known community and extended network. This shows that trust first begins with people and not data. Lastly, we demonstrate the barriers used by responding organizations have gone beyond discussions of trustworthiness and data quality to that of more operational issues.     

Synthesis, fabrication and characterization of poly[3-3′(vinylcarbazole)] (PVK) Langmuir-Schaefer films

Poly[3-3′(vinylcarbazole)] (PVK) was synthetized with N-vinylcarbazole as monomer by oxidative polymerization with ferric chloride. The resulting polymer was then deposited on various solid supports by using Langmuir-Schaefer (LS) method. The pressure-area isotherm of PVK revealed the possibility of compact monolayer formation at air-water interface. Different layers of PVK were doped with iodine vapours. Both scanning probe microscopy and optical microscopy images indicated a good uniformity of the films. The morphology and the thickness of PVK films were investigated using atomic force microscopy. The voltammetric investigation of I₂ doped PVK showed a distinctive electrochemical behaviour. The photoinduced charge transfer across a donor/acceptor (D/A) hybrid interface provided an effective method to study the photoelectrochemical properties of the composite LS films.     

A local landscape mapping method for protein structure prediction in the HP model

The hydrophobic-polar (HP) model has been widely studied in the field of protein structure prediction both for theoretical purposes and as a benchmark for new optimization strategies. In this work we present results of the recently proposed Hybrid Monte Carlo Ant Colony Optimization heuristic in the HP model using a fragment assembly-like strategy. Moreover we extend that method introducing a general framework for optimization in the HP model, called Local Landscape Mapping, and we test it using the pull moves set to generate solutions. We describe the heuristic and compare results obtained on well known HP instances in the 3-dimensional cubic lattice to those obtained with standard Ant Colony optimization and Simulated Annealing. Fragment assembly-like tests were performed using a modified objective function to prevent the creation of overlapping walks. Results show that our method performs better than the other heuristics in all benchmark instances when the fragment assembly-like strategy is used while in the case of pull moves-based neighborhood its performance is comparable to that of simulated annealing.     

Alder ene functionalization of polyisobutene oligomer and styrene-butadiene-styrene triblock copolymer

The Alder ene functionalization reaction of double bonds containing macromolecules such as polyisobutene oligomer (PIB) and a styrene-butadiene-styrene triblock copolymer (SBS) samples with maleic anhydride (MAH) or diethyl maleate (DEM) as enophiles is described. The analysis of the products by means of different techniques assesses the addition of the polar molecules to the reactive vinylidene units of the polymer with functional degrees (FD) depending on the type of enophile and polymer reactivity. The role of the reaction conditions and the use as Lewis acids as catalysts are discussed in terms of their influence on the addition reaction extent and on the polymer molecular weight.     

Modelling formation and growth of H2SO4-H2O aerosols: Uncertainty analysis and experimental evaluation

An aerosol dynamics model, AERO2, is presented, which describes the formation of H₂SO₄-H₂O aerosol in a smog chamber. The model is used to analyse how the uncertainties on four input parameters are propagated through an aerosol dynamics model. The input parameters are: the rate of the reaction between SO₂ and OH (k₁), the ratio between the nucleation rate used in AERO2 and that derived from classical nucleation theory (t_n), the H₂SO₄ mass accommodation coefficient () and a measure of the turbulence intensity in the reactor (k_e). Uncertainties for these parameters are taken from the literature. One of the results of the analysis is that AERO2 and aerosol dynamics models in general can only predict upper bounds for the total number (N_tot) and total volume (V_tot) concentrations of the particles. The uncertainties on N_tot and V_tot are mainly due to the uncertainties on k₁, and t_n. An uncertainty factor of 20–100 still remains when the uncertainty on k₁, is reduced to ±5%. Aerosol measurements from three smog chamber experiments have therefore been used, in an attempt to reduce the uncertainty on k₁ and t_n. Values for k₁ are obtained in the reduced range 7.8 × 10⁻¹³ to 1.0 × 10⁻¹² cm³ s⁻¹, which is within the range found in the literature. For t_n, values in the range 10⁴–10⁷ are obtained, which is close to the upper bound of the range in literature. These values for t_n are in marked contrast with a recent set of experiments on nucleation in H₂SO₄-H₂O mixtures, which suggests a value for t_n of at most 10⁻⁵.     

Evaluation of the antimicrobial action of honey against Staphylococcus aureus, Staphylococcus epidermidis, Pseudomonas aeruginosa, Escherichia coli, Salmonella enteritidis, Listeria monocytogenes and Aspergillus niger. Evaluation of its microbiological charge

The evaluation of the microbiological charge present in Costa Rican samples as the evaluation of its antimicrobial activity over different microorganisms, including those associated to wound infections, will allow to emit criteria referred to its use in therapeutic treatments, specially as alternative therapy for cases involving antibiotic resistant bacteria. The microbiological charge of 25 honey samples, acquired in Costa Rican markets was evaluated through several indicators including total plate aerobic count, total plate anaerobic count, total aerobic spore count, total anaerobic spore count and molds and yeast count. Also, samples were inoculated in tubes with chopped meat media and plated in egg yolk agar in order to determine the presence of Clostridium botulinum. For the antimicrobial activity evaluation, the diffusion method in Muller Hinton agar was performed, testing different honey concentrations (100, 75, 50, 25, 12,5 and 6,25 % v/v) against Staphylococcus aureus (ATCC 25923), Staphylococcus epidermidis (UCR 2902), Pseudomonas aeruginosa (ATCC 9027), Escherichia coli (ATCC25922), Salmonella enteritidis (ATCC 13076), Listeria monocytogenes (ATCC 19116) and Aspergillus niger. The results obtained for the microbiological characterization of honey show that 91% of samples had counts equal or lower than 1,0 x 10(1) CFU/g. No positive result was obtained for the isolation of C. botulinum. 24 of the samples analyzed inhibited the growth of S. aureus even in a 25% v/v concentration, nevertheless, A. niger was no inhibited by any of the samples tested.     

Influence of dietary long-chain PUFA on premature baboon lung FA and dipalmitoyl PC composition

One of the major survival challenges of premature birth is production of lung surfactant. The lipid component of surfactant, dipalmitoyl PC (DPPC), increases in concentration in the period before normal term birth via a net shift in FA composition away from unsaturates. We investigated the influence of dietary DHA and arachidonic acid (AA) on lung FA composition and DPPC concentration in term and preterm baboons. Pregnant animals/neonates were randomized to one of four groups: breast-fed (B), term formula-fed (T⁻), preterm formulafed (P⁻), and preterm fed formula supplemented with DHA-AA (P⁺). Breast milk contained 0.68%wt DHA and the P⁺ group formula contained 0.61%wt DHA. In the preterm groups (P⁻ and P⁺), pregnant females received a course of antenatal corticosteroids. At the adjusted age of 4 wk, neonate lung tissue was harvested, and FA composition and DPPC were analyzed. Palmitate was ∼28%wt of lung total FA and no significant differences were found among the four treatment groups. In contrast, DPPC in the B group lung tissue was significantly greater than DPPC in the unsupplemented groups, but not compared with the P⁺ group. The B and P⁺ groups were not significantly different in DHA and AA, but were different compared with the unsupplemented (T, P⁻) groups. These results indicate that LCP supplementation increases lung DHA and AA, without compromising overall lung 16∶0 or DPPC. The shift in FA composition toward greater unsaturation in the groups consuming LCP supported improved surfactant lipid concentration in preterm neonate lungs.     

Morphology and thermal properties of two polymethacrylates modified by a polymer liquid crystal

We have studied blends of a polymer liquid crystal (PLC) with poly(cyclohexylethyl methacrylate) (PCHEMA) or poly(cyclohexylpropyl methacrylate) (PCHPMA). The PLC is PET/0.6PHB where PET = poly(ethylene terephthalate), PHB = p-hydroxybenzoic acid and 0.6 is the mole fraction of the latter in the copolymer. The microstructure was studied by scanning electron microscopy (SEM). PCHEMA + PLC (20 wt% of the latter, blend E) has a fine texture with LC islands evenly distributed in the matrix and good adhesion between the phases resulting from their partial miscibility. The PCHPMA + PLC (20 wt% of the latter, blend P) shows only limited compatibility. The SEM results are confirmed by values of the glass transition temperatures T_g determined via thermal mechanical analysis. The T_g value of the blend E is shifted towards the T_g of PLC; T_g of blend P is practically equal to that of PCHPMA. The linear isobaric expansivity α_L values for both blends are lower than the respective values for pure PCHPMA and PCHEMA. Thermal stabilities of the blends determined by thermogravimetry are also better than those of pure polymethacrylates. The temperature of 50% weight degradation for blend E is higher than that for pure PCHEMA by more than 60 K Copyright © 2004 Society of Chemical Industry     

The KlaperSuite framework for model-driven reliability analysis of component-based systems

Automatic prediction tools play a key role in enabling the application of non-functional requirements analysis, to simplify the selection and the assembly of components for component-based software systems, and in reducing the need for strong mathematical skills for software designers. By exploiting the paradigm of Model-Driven Engineering (MDE), it is possible to automatically transform design models into analytical models, thus enabling formal property verification. MDE is the core paradigm of the KlaperSuite framework presented in this paper, which exploits the KLAPER pivot language to fill the gap between design and analysis of component-based systems for reliability properties. KlaperSuite is a family of tools empowering designers with the ability to capture and analyze quality of service views of their systems, by building a one-click bridge towards a number of established verification instruments. In this article, we concentrate on the reliability-prediction capabilities of KlaperSuite and we evaluate them with respect to several case studies from literature and industry.