Distance browsing in distributed multimedia databases

The state of the art of searching for non-text data (e.g., images) is to use extracted metadata annotations or text, which might be available as a related information. However, supporting real content-based audiovisual search, based on similarity search on features, is significantly more expensive than searching for text. Moreover, such search exhibits linear scalability with respect to the dataset size, so parallel query execution is needed.In this paper, we present a Distributed Incremental Nearest Neighbor algorithm (DINN) for finding closest objects in an incremental fashion over data distributed among computer nodes, each able to perform its local Incremental Nearest Neighbor (local-INN) algorithm. We prove that our algorithm is optimum with respect to both the number of involved nodes and the number of local-INN invocations. An implementation of our DINN algorithm, on a real P2P system called MCAN, was used for conducting an extensive experimental evaluation on a real-life dataset.The proposed algorithm is being used in two running projects: SAPIR and NeP4B.     

Online bin stretching with three bins

Online bin stretching is a semi-online variant of bin packing in which the algorithm has to use the same number of bins as an optimal packing, but is allowed to slightly overpack the bins. The goal is to minimize the amount of overpacking, i.e., the maximum size packed into any bin. We give an algorithm for online bin stretching with a stretching factor of \(11/8 = 1.375\) for three bins. Additionally, we present a lower bound of \(45/33 = 1.\overline{36}\) for online bin stretching on three bins and a lower bound of 19/14 for four and five bins that were discovered using a computer search.     

The joint movement of pebbles in solving the ($$N^2-1$$)-puzzle suboptimally and its applications in rule-based cooperative path-finding

The present paper deals with the problem of solving the (\(n^2 - 1\))-puzzle and cooperative path-finding (CPF) problems sub-optimally by rule-based algorithms. To solve the puzzle, we need to rearrange \(n^2 - 1\) pebbles in the \(n \times n\)-sized square grid using one vacant position to achieve the goal configuration. An improvement to the existing polynomial-time algorithm is proposed and experimentally analyzed. The improved algorithm represents an attempt to move pebbles in a more efficient way compared to the original algorithm by grouping them into so-called snakes and moving them together as part of a snake formation. An experimental evaluation has shown that the snakeenhanced algorithm produces solutions which are 8–9 % shorter than the solutions generated by the original algorithm. Snake-like movement has also been integrated into the rule-based algorithms used in solving CPF problems sub-optimally, which is a closely related task. The task in CPF consists in moving a group of abstract robots on an undirected graph to specific vertices. The robots can move to unoccupied neighboring vertices; no more than one robot can be placed in each vertex. The (\(n^2 - 1\))-puzzle is a special case of CPF where the underlying graph is a 4-connected grid and only one vertex is vacant. Two major rule-based algorithms for solving CPF problems were included in our study—BIBOX and PUSH-and-SWAP (PUSH-and-ROTATE). The use of snakes in the BIBOX algorithm led to consistent efficiency gains of around 30 % for the (\(n^2 - 1\))-puzzle and up to 50 % in for CPF problems on biconnected graphs with various ear decompositions and multiple vacant vertices. For the PUSH-and-SWAP algorithm, the efficiency gain achieved from the use of snakes was around 5–8 %. However, the efficiency gain was unstable and hardly predictable for PUSH-and-SWAP.     

Colour and rotation invariant textural features based on Markov random fields

A visual appearance of natural materials significantly depends on acquisition circumstances, particularly illumination conditions and viewpoint position, whose variations cause difficulties in the analysis of real scenes. We address this issue with novel texture features, based on fast estimates of Markovian statistics, that are simultaneously rotation and illumination invariant. The proposed features are invariant to in-plane material rotation and illumination spectrum (colour invariance), they are robust to local intensity changes (cast shadows) and illumination direction. No knowledge of illumination conditions is required and recognition is possible from a single training image per material. The material recognition is tested on the currently most realistic visual representation - Bidirectional Texture Function (BTF), using CUReT and ALOT texture datasets with more than 250 natural materials. Our proposed features significantly outperform leading alternatives including Local Binary Patterns (LBP, LBP-HF) and texton MR8 methods.     

Synthesis and characterization of ET(P)S-4 and ET(P)S-10

Phosphorus containing ET(P)S-4 and ET(P)S-10 were synthesized from gels of composition xNa₂O–0.6KF–0.2TiO₂–(1.28 − 4y)xHCl–yP₂O₅–1.49SiO₂–39.5H₂O at 190 °C for 3 days. The XRD patterns are almost identical to the corresponding ETS samples. The presence of phosphorus in the initial gel influences the kinetic parameters of the crystallization process, the morphology and the size of the crystals. The ³¹P-NMR of the samples show that part of the phosphorus is attached at the siliceous surface as dihydrogenophosphate SiOPO(OH)₂ groups and cannot be introduced in a tetrahedral or octahedral framework position.     

D-Index: Distance Searching Index for Metric Data Sets

In order to speedup retrieval in large collections of data, index structures partition the data into subsets so that query requests can be evaluated without examining the entire collection. As the complexity of modern data types grows, metric spaces have become a popular paradigm for similarity retrieval. We propose a new index structure, called D-Index, that combines a novel clustering technique and the pivot-based distance searching strategy to speed up execution of similarity range and nearest neighbor queries for large files with objects stored in disk memories. We have qualitatively analyzed D-Index and verified its properties on actual implementation. We have also compared D-Index with other index structures and demonstrated its superiority on several real-life data sets. Contrary to tree organizations, the D-Index structure is suitable for dynamic environments with a high rate of delete/insert operations.     

Approximate similarity retrieval with M-trees

Motivated by the urgent need to improve the efficiency of similarity queries, approximate similarity retrieval is investigated in the environment of a metric tree index called the M-tree. Three different approximation techniques are proposed, which show how to forsake query precision for improved performance. Measures are defined that can quantify the improvements in performance efficiency and the quality of approximations. The proposed approximation techniques are then tested on various synthetic and real-life files. The evidence obtained from the experiments confirms our hypothesis that a high-quality approximated similarity search can be performed at a much lower cost than that needed to obtain the exact results. The proposed approximation techniques are scalable and appear to be independent of the metric used. Extensions of these techniques to the environments of other similarity search indexes are also discussed. Received July 7, 1998 / Accepted October 13, 1998     

Chemical Markers of Human Tendon Health Identified Using Raman Spectroscopy: Potential for In Vivo Assessment

The purpose of this study is to determine whether age-related changes to tendon matrix molecules can be detected using Raman spectroscopy. Raman spectra were collected from human Achilles (n = 8) and tibialis anterior (n = 8) tendon tissue excised from young (17 ± 3 years) and old (72 ± 7 years) age groups. Normalised Raman spectra underwent principal component analysis (PCA), to objectively identify differences between age groups and tendon types. Certain Raman band intensities were correlated with levels of advanced glycation end-product (AGE) collagen crosslinks, quantified using conventional destructive biochemistry techniques. Achilles and tibialis anterior tendons in the old age group demonstrated significantly higher overall Raman intensities and fluorescence levels compared to young tendons. PCA was able to distinguish young and old age groups and different tendon types. Raman intensities differed significantly for several bands, including those previously associated with AGE crosslinks, where a significant positive correlation with biochemical measures was demonstrated. Differences in Raman spectra between old and young tendon tissue and correlation with AGE crosslinks provides the basis for quantifying age-related chemical modifications to tendon matrix molecules in intact tissue. Our results suggest that Raman spectroscopy may provide a powerful tool to assess tendon health and vitality in the future.     

The New Version of the ANDDigest Tool with Improved AI-Based Short Names Recognition

The body of scientific literature continues to grow annually. Over 1.5 million abstracts of biomedical publications were added to the PubMed database in 2021. Therefore, developing cognitive systems that provide a specialized search for information in scientific publications based on subject area ontology and modern artificial intelligence methods is urgently needed. We previously developed a web-based information retrieval system, ANDDigest, designed to search and analyze information in the PubMed database using a customized domain ontology. This paper presents an improved ANDDigest version that uses fine-tuned PubMedBERT classifiers to enhance the quality of short name recognition for molecular-genetics entities in PubMed abstracts on eight biological object types: cell components, diseases, side effects, genes, proteins, pathways, drugs, and metabolites. This approach increased average short name recognition accuracy by 13%.     

Chemistry towards Biology—Instruct: Snapshot

The knowledge of interactions between different molecules is undoubtedly the driving force of all contemporary biomedical and biological sciences. Chemical biology/biological chemistry has become an important multidisciplinary bridge connecting the perspectives of chemistry and biology to the study of small molecules/peptidomimetics and their interactions in biological systems. Advances in structural biology research, in particular linking atomic structure to molecular properties and cellular context, are essential for the sophisticated design of new medicines that exhibit a high degree of druggability and very importantly, druglikeness. The authors of this contribution are outstanding scientists in the field who provided a brief overview of their work, which is arranged from in silico investigation through the characterization of interactions of compounds with biomolecules to bioactive materials.