Comments on “Necessary and sufficient stability condition of fractional-order interval linear systems” [Automatica 44 (2008), 2985–2988]

This paper shows that the main thesis of the article “Necessary and sufficient stability condition of fractional-order interval linear systems” by Ahn and Chen (Automatica, vol. 44, pp. 2985–2988) is only a sufficient (and not a necessary) condition for the robust stability of fractional-order linear systems.     

Production of nanoparticles of copper compounds by anodic dissolution of copper in organic solvents

The anodic behaviour of copper was investigated in ethanol solution containing LiClO₄, LiCl electrolyte and water. The type of electrolyte and the water content influences the mechanism of the anodic process and the formation of anodic products. In LiClO₄ electrolyte the dissolution of copper is related to the oxidation of Cu(I) to Cu(II). In solutions of LiCl the etching of copper begins with the creation of soluble complexes of Cu(I) with chloride ions and solvent molecules. At potentials above 0.4 V the formation of alkoxides was observed in both solutions, characterized by a yellow tint. On the other hand, above 0.8 V (i.e. above the equilibrium potential of alcohol oxidation) copper dissolution is accompanied by the formation of a blue colloidal suspension of Cu (II) copper salt. Anodic etching of copper in solutions containing 3% H₂O at potentials higher than 0.4 V leads to the formation of colloidal suspension of copper oxide nanoparticles.     

Seed Selection for Spread of Influence in Social Networks: Temporal vs. Static Approach

The problem of finding optimal set of users for influencing others in the social network has been widely studied. Because it is NP-hard, some heuristics were proposed to find sub-optimal solutions. Still, one of the commonly used assumption is the one that seeds are chosen on the static network, not the dynamic one. This static approach is in fact far from the real-world networks, where new nodes may appear and old ones dynamically disappear in course of time. The main purpose of this paper is to analyse how the results of one of the typical models for spread of influence - linear threshold - differ depending on the strategy of building the social network used later for choosing seeds. To show the impact of network creation strategy on the final number of influenced nodes - outcome of spread of influence, the results for three approaches were studied: one static and two temporal with different granularities, i.e. various number of time windows. Social networks for each time window encapsulated dynamic changes in the network structure. Calculation of various node structural measures like degree or betweenness respected these changes by means of forgetting mechanism - more recent data had greater influence on node measure values. These measures were, in turn, used for node ranking and their selection for seeding. All concepts were applied to experimental verification on five real datasets. The results revealed that temporal approach is always better than static and the higher granularity in the temporal social network while seeding, the more finally influenced nodes. Additionally, outdegree measure with exponential forgetting typically outperformed other time-dependent structural measures, if used for seed candidate ranking.     

Online learning and fusion of orientation appearance models for robust rigid object tracking

We introduce a robust framework for learning and fusing of orientation appearance models based on both texture and depth information for rigid object tracking. Our framework fuses data obtained from a standard visual camera and dense depth maps obtained by low-cost consumer depth cameras such as the Kinect. To combine these two completely different modalities, we propose to use features that do not depend on the data representation: angles. More specifically, our framework combines image gradient orientations as extracted from intensity images with the directions of surface normals computed from dense depth fields. We propose to capture the correlations between the obtained orientation appearance models using a fusion approach motivated by the original Active Appearance Models (AAMs). To incorporate these features in a learning framework, we use a robust kernel based on the Euler representation of angles which does not require off-line training, and can be efficiently implemented online. The robustness of learning from orientation appearance models is presented both theoretically and experimentally in this work. This kernel enables us to cope with gross measurement errors, missing data as well as other typical problems such as illumination changes and occlusions. By combining the proposed models with a particle filter, the proposed framework was used for performing 2D plus 3D rigid object tracking, achieving robust performance in very difficult tracking scenarios including extreme pose variations.     

New method for the on-line signature verification based on horizontal partitioning

Verification of identity based on the analysis of dynamic signatures is an important problem of biometrics. The effectiveness of the verification significantly increases when the dynamic characteristics of signature (e.g. velocity of the pen) are considered. These characteristics are individual for each user and difficult to imitate. The effectiveness of the verification can be further improved by using partitioning. In this paper we propose a new method which uses partitioning. In our method partitions represent areas of high and low speed of signature and high and low pen?s pressure. All selected partitions are used by our algorithm, but more important in the classification process are these partitions, in which the signatures of the user acquired during training phase are more stable. Moreover, final classification is interpretable. In this paper we present the simulation results of the proposed method for the two databases: SVC2004 and BioSecure Database.     

Quality assessment for a visual and automatic license plate recognition

Video transmission and analysis is often utilized in applications outside of the entertainment sector, and generally speaking this class of video is used to perform specific tasks. Examples of these applications include security and public safety. The Quality of Experience (QoE) concept for video content used for entertainment differs significantly from the QoE of surveillance video used for recognition tasks. This is because, in the latter case, the subjective satisfaction of the user depends on achieving a given functionality. Recognizing the growing importance of video in delivering a range of public safety services, we focused on developing critical quality thresholds in license plate recognition tasks based on videos streamed in constrained networking conditions. Since the number of surveillance cameras is still growing it is obvious that automatic systems will be used to do the tasks. Therefore, the presented research includes also analysis of automatic recognition algorithms.     

Isolation and amino acid sequence of a serine proteinase inhibitor from common flax (Linum usitatissimum) seeds

LUTI (Linum usitatissimum trypsin inhibitor), a member of the potato inhibitor I family, has been isolated from seeds of flax by ethanol fractionation, ion exchange chromatography on CM-Sephadex C-25, affinity purification on immobilized methylchymotrypsin (alpha-chymotrypsin in which His57 has been converted to 3-methylhistidine) in the presence of 5M NaCl, and finally by reversed-phase HPLC. The 7655 Da inhibitor consists of a single polypeptide chain of 69 residues with one disulfide bridge. The molecule is acetylated at the N terminus. Its primary structure has been determined after limited proteolysis of the native molecule with trypsin at the reactive site, cleavage with cyanogen bromide or arginyl endopeptidase (Arg-gingipain), and alcoholytic deacetylation of the N-terminally blocked serine. The association constants (K(a)) of LUTI with bovine beta-trypsin and alpha-chymotrypsin are 3.58x10(10) M(-1) and 5.02x10(5) M(-1), respectively. High NaCl concentration (3M) increased the association constant of LUTI with alpha-chymotrypsin to 6.64x10(7) M(-1). To our knowledge, LUTI is the first serine-proteinase-type inhibitor isolated from a plant of the Linaceae family.