Search

Search Results

• SYNTHESIS OF SOFTWARE AND INFORMATION SUPPORT FOR THE IMPLEMENTATION OF METHODS FOR VERIFICATION OF THE STATE OF MEDICAL BIOLOGICAL OBJECTS FOR A MEDICAL AUTOMATED INFORMATION SYSTEM

  А. V. Proskuryakov

  2022-05-26

  Abstract ▼

  This article describes the information and software for the implementation of various methods
  for verifying the state of fragments of biological objects using computed tomographic images by the
  decision support subsystem for the diagnosis of diseases. It is pointed out the current state of development
  of medical diagnostic equipment, the equipment of which medical institutions of the country
  and its non-operational accessibility to the population contributed to and led to the emergence and
  active development of new directions in the field of radiation diagnostics, which include: digital and
  film radiography, computed tomography, magnetic resonance imaging. The article focuses on the
  analysis of X-ray images, decision-making based on the analysis of these images, diagnosis based on
  the decisions made. The advantages and disadvantages of radiography as a modern diagnostic method
  are analyzed relative to their analogues. An important task in the analysis of radiographic images
  of medical biological objects and their fragments is to solve the problem of image quality improvement.
  In order to improve the quality of X-ray images and increase their informativeness, an algorithm
  has been developed and the software of the software subsystem of the medical automated information
  system for their correction and analysis has been implemented. The article discusses the
  implementation of solving problems of diagnosis of diseases, such as: analysis of radiographic images,
  decision-making based on the analysis of these images, diagnosis based on the decisions made by
  developing and applying software and information support for the implementation of methods for
  verifying the state of fragments of biological objects as effective methods for diagnosing the state of
  paranasal sinuses by their radiographic and computed tomographic images. The main methods underlying
  verification by X-ray and computed tomography images are described. A detailed analysis
  of the implementation of mathematical models of diagnostic methods in the form of algorithms implemented
  by software for the functioning of the decision support subsystem of a medical automated
  information system is given. Examples of practical implementation of software and information support
  for verification methods of medical objects in the form of screen forms for working with fragments
  of the object under study and the results of the analysis of radiographic images are shown.
  This makes it possible to increase the efficiency, accuracy of verification of the state of medical biological
  objects, the reliability of the disease diagnosis process. The scientific novelty, the results of
  the approbation of the material presented in the article at international, All-Russian conferences,
  scientific journals are shown.

• COMPUTATIONAL FORENSICS METHODOLOGY AND FORMAL VERIFICATION OF EXPERT FINDINGS

  Е.S. Abramov

  45-68

  2026-07-07

  Abstract ▼

  This paper addresses the fundamental challenge of overcoming the systemic epistemological crisis in digital forensics. This crisis is driven by an expanding semantic gap between the probabilistic and stochastic nature of digital traces—frequently compromised by anti-forensic techniques—and the rigorous demands of adversarial legal proceedings for the legal certainty of evidence. The article is conceptual in nature and establishes the theoretical foundation of computational forensics as an independent scientific discipline. The study justifies a necessary paradigm shift from traditional heuristic artifact-discovery approaches and subjective expert opinions toward a rigorous methodology grounded in the principles of algorithmic reproducibility, the measurability of uncertainty, and formal verifiability. The author develops a set-theoretic ontological model of a computer incident, which is built upon the "subject–method–object" (S-M-O) triad and the axiom of process trace conservation. This model enables a one-to-one mapping of low-level technical indicators (IoA, IoB, IoC) onto the legal elements of a crime (corpus delicti). Furthermore, a methodology for the formal verification of hypothesis validity is proposed, incorporating the criteria of structural completeness, causal coherence, logical consistency, and factual grounding. For the first time, a mathematical model for assessing the reliability of expert findings using a logistic function (trust function) is introduced into scientific discourse. This model enables the calculation of the probability of a juridical fact by aggregating taxonomic compliance metrics, the strength of causal relationships within the incident graph, and an environmental entropy penalty. The application of the developed approach transforms forensic incident reconstruction from an ill-posed inverse problem into a deterministic procedure, ensuring the mathematically provable objectivity of the evidentiary base even under conditions of incomplete data and active anti-forensic countermeasures.

• VERIFICATION OF DYNAMIC BIOMETRIC PARAMETERS OF A PERSONALITY BASED ON A PROBABLE NEURAL NETWORK

  Y.A. Bryuhomitsky

  2021-01-19

  Abstract ▼

  Biometric identity verification is used primarily for access to computer and mobile systems, as
  well as for remote (voice) verification. In fact, the most widespread systems are biometric verification
  systems based on a fixed passphrase, which are quite simple to implement, but very vulnerable to
  attacks of reproduction of a compromised short text. To eliminate this drawback, it is proposed to
  carry out identity verification using a text that is arbitrary in terms of volume, content and language
  (text-independent biometric verification). This paper proposes a generalized approach to solve the
  problem of identity verification by dynamic biometric parameters of different modality (keyboard
  writing, handwriting, voice). The presentation of dynamic biometrics signals is carried out by converting
  them into a sequences of information units, each of which contains the same number of counts
  of biometric signal of corresponding modality. The solution to this problem is carried out by monitoring
  the degree of concentration of closely located information units (clusters) at certain points of the
  multidimensional feature space. Such control is implemented on a probabilistic neural network thatstatistically evaluates the probability density of the distribution of information units in the corresponding
  clusters with the subsequent determination of the total probability density for the entire
  class of objects. The advantages of the proposed approach are: generalization of substantially different
  methods of text-independent identity verification by dynamic biometric parameters of different
  modality; the ability to make a verification decision for a fixed time of receipt of biometric data, determined
  by the size of the model used; the ability to set the verification accuracy by changing the
  dimension of the layer of probabilistic network samples. The disadvantage of the proposed approach
  is the need for software implementation of a large-scale neural network. However, this drawback is
  quickly leveled with an increase in the productivity of computer technology.