Information Compression Research Articles

Research on an Improved Adaptive Fitting Algorithm of Trajectory Information

In order to facilitate the storage, visualization and data mining of large-scale trajectory information, an improved adaptive fitting algorithm of trajectory information is proposed, which can automatically select the optimal fitting interval and generate the key points and coefficients of the fitted interval. The algorithm consists of two steps: Firstly, the adaptive fitting method is used to fit the trajectory points to obtain the most suitable fitted trajectory interval, and the fitting method adopts the least squares method. Secondly, the constrained quadratic programming method is used to optimize the obtained trajectory interval coefficients to make the fitting curve smooth and continuous. The experimental simulation proves that the algorithm has obvious effects on data compression and feature extraction of trajectory information.

Haptic Codecs for the Tactile Internet

The Tactile Internet will enable users to physically explore remote environments and to make their skills available across distances. An important technological aspect in this context is the acquisition, compression, transmission, and display of haptic information. In this paper, we present the fundamentals and state of the art in haptic codec design for the Tactile Internet. The discussion covers both kinesthetic data reduction and tactile signal compression approaches. We put a special focus on how limitations of the human haptic perception system can be exploited for efficient perceptual coding of kinesthetic and tactile information. Further aspects addressed in this paper are the multiplexing of audio and video with haptic information and the quality evaluation of haptic communication solutions. Finally, we describe the current status of the ongoing IEEE standardization activity P1918.1.1 which has the ambition to standardize the first set of codecs for kinesthetic and tactile information exchange across communication networks.

FPGA Based Implementation of ImageZero Compression Algorithm

The main goal of information compression is to achieve the greatest reduction possible of the volume of data. This action affects both storage and transmission. However, the most used algorithms have considerable latency and are not practical for real-world applications. In the image compression field, the situation is more complex because the resolutions are constantly increasing. Nowadays, it is common to deal with uncompressed images that exceed 60 MB. Dedicated compressors present strong restrictions of time, space and power so a thorough design and development should be made. In this article, an architecture of ImageZero compression lossless algorithm is presented. The algorithm was selected for its low latency both in encoding and decoding. The novelty of this work is the hardware implementation for this algorithm, based on FPGA. The synthesis results demonstrate that an increase in input image resolution does not affect the compression speedup. Also, the throughput for this proposal is greatest than other hardware implementations of image compressors.

Evaluation of Clustering Methods in Compression of Topological Models and Visual Place Recognition Using Global Appearance Descriptors

This paper presents an extended study about the compression of topological models of indoor environments. The performance of two clustering methods is tested in order to know their utility both to build a model of the environment and to solve the localization task. Omnidirectional images are used to create the compact model, as well as to estimate the robot position within the environment. These images are characterized through global appearance descriptors, since they constitute a straightforward mechanism to build a compact model and estimate the robot position. To evaluate the goodness of the proposed clustering algorithms, several datasets are considered. They are composed of either panoramic or omnidirectional images captured in several environments, under real operating conditions. The results confirm that compression of visual information contributes to a more efficient localization process through saving computation time and keeping a relatively good accuracy.

Study of Subjective and Objective Quality Evaluation of 3D Point Cloud Data by the JPEG Committee

The SC29/WG1 (JPEG) Committee within ISO/IEC is currently working on developing standards for the storage, compression and transmission of 3D point cloud information. To support the creation of these standards, the committee has created a database of 3D point clouds representing various quality levels and use-cases and examined a range of 2D and 3D objective quality measures. The examined quality measures are correlated with subjective judgments for a number of compression levels. In this paper we describe the database created, tests performed and key observations on the problems of 3D point cloud quality assessment.

Information Compression as a Unifying Principle in Human Learning, Perception, and Cognition

This paper reviews evidence for the idea that much of human learning, perception, and cognition may be understood as information compression and often more specifically as “information compression via the matching and unification of patterns” (ICMUP). Evidence includes the following: information compression can mean selective advantage for any creature; the storage and utilisation of the relatively enormous quantities of sensory information would be made easier if the redundancy of incoming information was to be reduced; content words in natural languages, with their meanings, may be seen as ICMUP; other techniques for compression of information—such as class‐inclusion hierarchies, schema‐plus‐correction, run‐length coding, and part‐whole hierarchies—may be seen in psychological phenomena; ICMUP may be seen in how we merge multiple views to make one, in recognition, in binocular vision, in how we can abstract object concepts via motion, in adaptation of sensory units in the eye of Limulus, the horseshoe crab, and in other examples of adaptation; the discovery of the segmental structure of language (words and phrases), grammatical inference, and the correction of over‐ and undergeneralisations in learning may be understood in terms of ICMUP; information compression may be seen in the perceptual constancies; there is indirect evidence for ICMUP in human cognition via kinds of redundancy such as the decimal expansion of π which are difficult for people to detect; much of the structure and workings of mathematics—an aid to human thinking—may be understood in terms of ICMUP; and there is additional evidence via the SP Theory of Intelligence and its realisation in the SP Computer Model. Three objections to the main thesis of this paper are described, with suggested answers. These ideas may be seen to be part of a “Big Picture” with six components, outlined in the paper.

Mathematics as Information Compression via the Matching and Unification of Patterns

This paper describes a novel perspective on the foundations of mathematics: how mathematics may be seen to be largely about “information compression (IC) via the matching and unification of patterns” (ICMUP). That is itself a novel approach to IC, couched in terms of nonmathematical primitives, as is necessary in any investigation of the foundations of mathematics. This new perspective on the foundations of mathematics reflects the facts that mathematics is almost exclusively the product of human brains, and has been developed, as an aid to human thinking, mathematics is likely to be consonant with much evidence for the importance of IC in human learning, perception, and cognition. This perspective on the foundations of mathematics has grown out of a long‐term programme of research developing the SP Theory of Intelligence and its realization in the SP Computer Model, a system in which a generalised version of ICMUP—the powerful concept of SP-multiple-alignment—plays a central role. This paper shows with an example how mathematics, without any special provision, may achieve compression of information. Then, it describes examples showing how variants of ICMUP may be seen in widely used structures and operations in mathematics. Examples are also given to show how several aspects of the mathematics‐related disciplines of logic and computing may be understood as ICMUP. Also discussed is the intimate relation between IC and concepts of probability, with arguments that there are advantages in approaching AI, cognitive science, and concepts of probability via ICMUP. Also discussed is how the close relation between IC and concepts of probability relates to the established view that some parts of mathematics are intrinsically probabilistic, and how that latter view may be reconciled with the all‐or‐nothing, “exact,” forms of calculation or inference that are familiar in mathematics and logic. There are many potential benefits and applications of the mathematics‐as‐IC perspective.

3D Surface Matching by a Voxel-Based Buffer-Weighted Binary Descriptor

3D surface matching by local feature descriptors is a fundamental task in 3D object registration, recognition, and retrieval. In view of 2D projected descriptors’ information compression and 3D directly voxelized descriptors’ sensitivity to density variation and boundary, this paper first proposes a voxel-based buffer-weighted binary descriptor, named VBBD. After local surfaces of detected keypoints are voxelized, each voxel’s buffer region is established, and the buffer-weighted Gaussian kernel density is calculated. If the current voxel’s buffer-weighted density is larger than its local surface’s average density, the voxel is labeled 1, otherwise, it is 0. The proposed descriptor has several merits: 1) direct acquisition of 3D information without projection, the neighbor information is less compressed. 2) voxels are labeled and binarized according to the buffer-weighted density, which improves the robustness to boundary effect, noise and density variation. Based on the VBBD, a global optimal surface matching method based on a Kuhn_Munkres (KM) algorithm is adopted. The strategy has several advantages: 1) by calculating the descriptors of large-scaled surfaces which are down sampled, the number of the point cloud is reduced, and meanwhile, large-scaled information is obtained; and 2) KM algorithm is adopted to find matching pairs to achieve final maximum weight sum of all matching pairs, which can efficiently avoid local optimum. The experimental results show that, compared with other state-of-the-art descriptors, the VBBD has better descriptiveness and robustness, and the surface matching strategy by the VBBD can achieve both high recall and precision.

Translation and Localization: On Translation Compression and Extension of Information

This paper considers the problem of completeness of information transfer during translation; the latter is understood as a type of communicative activity on transposing full-value verbal messages from one culture (and language) into another culture (and language). The main attention is devoted to the translation transformations of compression, or contraction, and extension of information. The viewpoint that the term “translation with elements of localization” is valid is supported. The analysis is based on authentic texts of scientific, technical, and business literature.

ПОЛУПРЕДИКАТИВНЫЕ КОНСТРУКЦИИ КАК СРЕДСТВО КОМПРЕССИИ ИНФОРМАЦИИ В ПОРТРЕТНЫХ ОПИСАНИЯХ А.П. ЧЕХОВА

The article based on the portrait descriptions in A.P. Chekhovprose analyzes syntactic units, among which the most commonly used (70% of the total) syntactic units used by the writer for creating a collapsed portrait are semi-predicative constructions. It is explained by the tendency of the author of the short storiesto compress the narration using saving semi-predicative constructions to submit language material. Special attention in the analysis of semi-predicative constructions – noun phrases, adverbial participial phrases and participial phrases, is given to separate definitions that perform as functional semantic equivalent of definitive clause and serve to name or clarify age, social status, nationality, official position, degree of kinship and even the nameof the character. Semi-predicative constructions are seen not only as a means for “representation”of a new character in the narration, but also as a compact means of text formation in the character’s portrait chain. Although the maximum length of the folded portrait in prose of A.P. Chekhov does not exceed four components, they increase the informative content of the phrase, give it a special rhythm, make it easy to perceive and o pronounce. Key words: semi-predicative constructions, information compression, separate definitions, substantive, participial and adverbial phrases, applications, compressed character portrait.

ПЕДАГОГИЧЕСКИЕ УСЛОВИЯ РЕАЛИЗАЦИИ КОМПЛЕКСА МОДЕЛЕЙ ФОРМИРОВАНИЯ ГОТОВНОСТИ КУРСАНТОВ К РЕШЕНИЮ КОМПЕТЕНТНОСТНО-ОРИЕНТИРОВАННЫХ ПРОФЕССИОНАЛЬНЫХ ЗАДАЧ

Competence-oriented professional tasks reflect the substantive and procedural aspect of future officers training to fulfill official duties. We identified and justified the necessary and sufficient pedagogical conditions that in complex can increase the effectiveness of introducing into the educational process of military educational institutions a set of models to form students' readiness to solve competence-oriented professional tasks. The application of the following research methods contributed to the solution of the task: studying, analyzing and summarizing the experience of organizing and improving the educational process of military educational organizations, as well as training of the future military aviation specialist (military navigator and combat control officer). The complex of pedagogical conditions embodies: 1) the formation of the subjective cognitive experience of students using diagnostic problem solving; 2) the use of graphical methods of compression and presentation of educational information to form and develop a system of operational information on the cycles of disciplines; 3) the motivation growth of students through the use of checklists for the implementation of the reflection process of solving problems. The novelty of the results is determined by the combination and essence of the pedagogical conditions identified taking into account the methodological basis of the designed complex of models, features and patterns of both the educational process of military educational institutions of higher education of the RF Ministry of Defense, and the process of solving competenceoriented tasks by cadets along with their individual characteristics. The significance of the results obtained is that the introduction of the identified set of pedagogical conditions can increase the effectiveness of introducing a set of models of cadets’ readiness formation to solve competence- oriented professional tasks.

Ways of cognitive information compression in a popular science text

Ways of cognitive information compression in a popular science text

Helping Hadamard conjecture to become a theorem. Part 1

Introduction:Hadamard conjecture about the existence of specific square matrices was formulated not by Hadamard but by other mathematicians in the early 20th century. Later, this problem was revised by Ryser together with Bruck and Chowla, and also by Hall, one of the founders of discrete mathematics. This is a problem of the boundary mixed type, as it includes both the continuous and discrete components. The combinatorial approach used in the framework of the discrete component has run its course by the end of the century. The article discusses an alternative based on both concepts.Purpose:To analyze the reasons why the conjecture about the existence of Hadamard matrices of all orders n = 4t is considered unproven, and to propose possible ways to prove it.Methods:Transition, by lowering the order n = 4t– 2, to two-level quasiorthogonal matrices with elements 1 and –b whose existence on all specified orders is not a difficult problem due to the possible irrationality of their entries. Subsequent construction of a chain of transformations to matrix orders n = 4t – 1, n = 4t, n = 4t + 1.Results:It is proved that Gauss points on an x2+ 2y2+ z2= n spheroid are in one-to-one correspondence with symmetric Hadamard matrices (constructed on the basis of the Balonin — Seberry arrays), covering up the gaps on the unsolvable orders 140, 112, etc. known in Williamson’s array theory. Solution tables are found and systematized, which include so-called «best» three-block matrices L (p, q), where p ≥ q is the number of non-conjugated symmetric matrices of the order in question, and q is the number of block-symmetric matrices which coincide with Williamson’s solutions. The iterative Procrustes algorithm which reduces the norm of the maximum entry in a matrix is proposed for obtaining Hadamard matrices by searching for local and global conditional extremes of the determinant.Practical relevance:The obtained Hadamard matrices and quasi-orthogonal matrices of orders n = 4t – 2, n = 4t – 1, n = 4t + 1 are of immediate practical importance for the problems of noise-resistant coding, compression and masking of video information.

Community discovery method based on complex network of data fusion based on the super network perspective

ABSTRACT To enhance the computational efficiency and precision of community discovery, a community discovery algorithm with the mixed label based on the minimum description length (MDI) of information compression is proposed in this paper. Firstly, the community detection is converted to the information compression problem of seeking for an effective network structure and the quality evaluation function is constructed based on the MDL criterion. Secondly, the community discovery algorithm with heuristic mixed label movement is constructed based on the label node movement algorithm and Louvain community addition algorithm so as to reduce the quality evaluation function. Finally, the simulation experiment in the standard test set and API capture Sina microblog dataset shows that the proposed algorithm is superior to the selected comparison algorithm in computational efficiency and precision.

Abstracting lexocigraphical works

The increasing interest towards abstracting as a type of analytical and synthetical information processing due to science globalization trend, is emphasized. The professionals who study this primary information compression are bibliographers, linguists, and information specialists. The author argues that modern professors and students all have to and must learn abstracting in accordance with the international standards for scientific, research, reference and instructional works.The author points to the diversity of the national lexicographical studies and, based on the abstracts index obtained as a result of her study, characterizes the current trends in abstracting linguistic dictionaries. The key user groups are defined. Publishers’ abstracts of dictionaries are discussed and represented. The example of dictionary Internet-based abstract analysis is given (50 items). Based on the abstracts texts, main negative factors to impact information value of this secondary information source are revealed, that is: lacking data essential for users, incomplete description of targeted readership, etc.The author introduces a model plan for digital guides of Russian lexicographical works and complements the plan with the systematic aspect analysis. She concludes that abstracting is an intellectually intensive process. It is underexplored as far as lexicographical works are concerned, and offers many possibilities for further studies.

DBN Structure Design Algorithm for Different Datasets Based on Information Entropy and Reconstruction Error.

Deep belief networks (DBNs) of deep learning technology have been successfully used in many fields. However, the structure of a DBN is difficult to design for different datasets. Hence, a DBN structure design algorithm based on information entropy and reconstruction error is proposed. Unlike previous algorithms, we innovatively combine network depth and node number and optimizes them simultaneously. First, the mathematical model of the structural design problem is established, and the boundary constraint for node number based on information entropy is derived by introducing the idea of information compression. Moreover, the optimization objective of the network performance based on reconstruction error is proposed by deriving the fact that network energy is proportional to reconstruction error. Finally, the improved simulated annealing (ISA) algorithm is used to adjust the DBN network layers and nodes simultaneously. Experiments were carried out on three public datasets (MNIST, Cifar-10 and Cifar-100). The results show that the proposed algorithm can design its proper structure to different datasets, yielding a trained DBN which has the lowest reconstruction error and prediction error rate. The proposed algorithm is shown to have the best performance compared with other algorithms and can be used to assist the setting of DBN structural parameters for different datasets.

On the Systematics and Scale for Measuring Historical Pathways of the Development of Morphological Diversity

Parametrical classification of elementary units of multicellularity (of histiones), looking like a periodic table, is proposed. It allows both estimation and prediction of the development of histiones. In addition, it compactly reflects extensive phenomenology of development, deriving it from a few principles and, hence, allowing compression of information. The system of histiones included in the table is also represented as a circular diagram, and it is shown that adequate consideration of this set requires the use of at least five scales.

Selective maintenance of value information helps resolve the exploration/exploitation dilemma

In natural environments with many options of uncertain value, one faces a difficult tradeoff between exploiting familiar, valuable options or searching for better alternatives. Reinforcement learning models of this exploration/exploitation dilemma typically modulate the rate of exploratory choices or preferentially sample uncertain options. The extent to which such models capture human behavior remains unclear, in part because they do not consider the constraints on remembering what is learned.Using reinforcement-based timing as a motivating example, we show that selectively maintaining high-value actions compresses the amount of information to be tracked in learning, as quantified by Shannon's entropy. In turn, the information content of the value representation controls the balance between exploration (high entropy) and exploitation (low entropy). Selectively maintaining preferred action values while allowing others to decay renders the choices increasingly exploitative across learning episodes.To adjudicate among alternative maintenance and sampling strategies, we developed a new reinforcement learning model, StrategiC ExPloration/ExPloitation of Temporal Instrumental Contingencies (SCEPTIC). In computational studies, a resource-rational selective maintenance approach was as successful as more resource-intensive strategies. Furthermore, human behavior was consistent with selective maintenance; information compression was most pronounced in subjects with superior performance and non-verbal intelligence, and in learnable vs. unlearnable contingencies. Cognitively demanding uncertainty-directed exploration recovered a more accurate representation in simulations with no foraging advantage and was strongly unsupported in our human study.

A hexagonal Fourier model of grid cells.

Grid cells in rat medial entorhinal cortex are widely thought to play a major role in spatial behavior. However, the exact computational role of the population of grid cells is not known. Here we provide a descriptive model, which nonetheless considers biologically feasible mechanisms, whereby the grid cells are viewed as a two-dimensional Fourier basis set, in hexagonal coordinates, with restricted availability of basis functions. With known properties imposed in the model parameters, we demonstrate how various empirical benchmark findings are straight-forward to understand in this model. We also explain how complex computations, inherent in a Fourier model, are feasible in the medial entorhinal cortex with simple mechanisms. We further suggest, based on model experiments, that grid cells may support a form of lossy compression of contextual information, enabling its representation in an efficient manner. In sum, this hexagonal Fourier model suggests how the entire population of grid cells may be modeled in a principled way, incorporates biologically feasible mechanisms and provides a potentially powerful interpretation of the relationship between grid-cell activity and contextual information beyond spatial knowledge. This enables various phenomena to be modeled with relatively simple mechanisms, and leads to novel and testable predictions.

Algebraic Properties of Cores of Generalized Neurofunctions

This paper considers generalized neural elements and identifies the conditions for implementation of functions of algebra of logic from these elements. We introduce the concept of a modified core of Boolean functions with respect to the system of characters of a group on which functions of algebra of logic are given. The criteria of belonging these functions to the class of generalized neurofunctions are provided. The algebraic structure of cores of Boolean neurofunctions is studied. On the basis of properties of tolerance matrices, a number of necessary conditions for implementation of Boolean functions by one generalized neural element are obtained. The obtained results allow to develop efficient methods of synthesis of integer-valued generalized neural elements with a large number of inputs that can be successfully applied in solving information compression and transmission problems, as well as discrete signal recognition problems.