Hasil untuk "Cybernetics"

Marek Biernacki, Katarzyna Ostasiewicz

ObjectivesThis study aimed to verify the hypothesis that the improvement in the subjective assessment of population health in certain European countries after the COVID-19 pandemic was driven by the mortality of the majority of vulnerable citizens with the worst health status.MethodsWe extended the trend of the share of the oldest age group and compared it with the observed fraction, thereby identifying the “missing population.”ResultsWe observed a substantial deficit in the population of the oldest age group, especially in countries where people tend not to age well.ConclusionThe temporary improvement in population health indicators, as measured by Healthy Life Years (HLY), during the pandemic in some countries was most likely an artifact resulting from the mortality of the majority of vulnerable individuals with poor health status. It is unlikely that this apparent improvement reflects healthier lifestyles or genuine gains in the efficiency or resilience of health systems during the pandemic. Therefore, the interpretation and use of HLY values from the COVID-19 period in Europe should be carefully reconsidered and further validated.

Oleksandr Kuznietsov , Oleksii Kolomiitsev , Ivan Nos et al.

Sea-based radar stations (RS) are widely used for solving the tasks of radar surveillance of surface objects (SO) and air objects (AO). The subject of the article is the mechanisms of radio wave propagation in the boundary layer of the atmosphere. The aim is to investigate the possibilities of improving the accuracy of measuring the range and radial velocity of SO and AO observed beyond the line-of-sight of coastal-based RS. Objective: to analyse the spatial and temporal parameters and properties of waveguide layers above the water surface. Methods used: maximum likelihood and frequency. The following results were obtained. The results of experimental studies of seasonal and daily changes in the parameters of the lower troposphere layer in the Black Sea coastal zone and the parameters of tropospheric radio waveguides are presented. The procedure for calculating the energy transmission losses during radio wave propagation in the boundary layer of the atmosphere is presented, and the conditions for detecting SO and AO beyond the radar line-of-sight are determined. Recommendations for increasing the range of detection of SO and AO are given, which are associated with the possibility of predicting the existence of tropospheric radio waveguides by using data on the current conditions of radio wave propagation over the sea based on the signals of the automatic ship identification system AIS. Conclusions. Proposals have been developed to improve the accuracy of measuring the range and radial velocity of SO and AO at waveguide propagation of radio waves over the sea surface. A promising area for further research may be to identify ways to optimise the measurement of angular coordinates in modern RS during waveguide propagation of radio waves over the sea surface.

Vanita Agrawal, Jayant Jagtap, M.V.V. Prasad Kantipudi

Handwritten document recognition and classification are among the many computers related issues being studied for digitizing handwritten data. A handwritten document comprises text, diagrams, mathematical expressions, numerals, and tables. Due to the variety of writing styles and the intricacy of the written language, it has proven difficult to recognize handwritten material. As a result, numerous handwritten document recognition systems have been developed, each with unique benefits and drawbacks. The paper reviews the evolution of handwritten document recognition in qualitative and quantitative ways. Initially, the bibliometric survey is presented based on the number of articles, citations, countries, authors, etc., on handwritten document recognition in the Scopus database. Later, a survey is done on the learning techniques used for handwritten documents: text recognition, digit recognition, mathematical expression recognition, table recognition, and diagram recognition. This paper also presents the directions for future research in handwritten document recognition.

Alexander I. Tolstoy

Based on the previously accepted taxonomy of concepts, a classification of concepts is proposed that is related to cybersecurity (CS) of objects and currently has the maximum unambiguous correspondence between the terms denoting these concepts and the concepts themselves. When constructing the classification, an attempt was made to apply the fundamentals of the taxonomy theory (systematics), the results of which led to the conclusion that the considered structures of concept systems will be hierarchical (the basic principle of taxonomy) under certain conditions (for example, when using only concepts that relate to the categories of the subject (object)), process, or property). The approach considered made it possible to form a group of terms directly related to the concepts from the proposed classification. This set can be considered as a terminology system related to the object’s CS. The proposed terms and their definitions do not contradict similar ones being used, but are distinguished by consistency in relation to the terms (definitions) themselves and corresponding concepts, and also have a universal application, which allows their use for almost any CS objects related to information (for example, information and automated systems, informatization systems, sociotechnical systems, cyber-physical systems and information as an object). The results obtained also have practical significance for education in the formation of a modern, methodologically sound conceptual base of students.

A.I. Yurin, G.N. Vishnyakov, V.L. Minaev

Methods for measuring the refractive index of optically transparent dielectric materials are considered. Modified methods based on the methods of minimum deviation and constant deviation are proposed and allow determining the refractive index of triangular prisms with unknown apex angles. In the proposed methods, the angles of light deviation on three faces of the prism are measured, and the refractive index of the material and the prism angles are determined from the solution of a system of equations. To implement the proposed methods, a goniometric system is used. That system was designed to measure angles between the flat surfaces of objects in manual and automated modes. Reference prism samples made of N-SF 1 optical glass, and a hollow prism filled with distilled water are studied. The proposed methods are compared and the measurement error is estimated. It is shown that the modified methods can be used for high-precision measurements of the refractive index in cases where the angles of the prism are unknown, or their measurement is associated with technical difficulties.

Tinnathi Sreenivasu, Sudhavani G.

In this work a model is introduced to improve forgery detection on the basis of superpixel clustering algorithm and enhanced Grey Wolf Optimizer (GWO) based AlexNet. After collecting the images from MICC-F600, MICC-F2000 and GRIP datasets, patch segmentation is accomplished using a superpixel clustering algorithm. Then, feature extraction is performed on the segmented images to extract deep learning features using an enhanced GWO based AlexNet model for better forgery detection. In the enhanced GWO technique, multi-objective functions are used for selecting the optimal hyper-parameters of AlexNet. Based on the obtained features, the adaptive matching algorithm is used for locating the forged regions in the tampered images. Simulation outcome showed that the proposed model is effective under the conditions: salt & pepper noise, Gaussian noise, rotation, blurring and enhancement. The enhanced GWO based AlexNet model attained maximum detection accuracy of 99.66%, 99.75%, and 98.48% on MICC-F600, MICC-F2000 and GRIP datasets.

X. Xu, X. Huang, J. Sun et al.

Whether for cancer diagnosis or single-cell analysis, it remains a major challenge to isolate the target sample cells from a large background cell for high-efficiency downstream detection and analysis in an integrated chip. Therefore, in this paper, we propose a 3D-stacked multistage inertial microfluidic sorting chip for high-throughput enrichment of circulating tumor cells (CTCs) and convenient downstream analysis. In this chip, the first stage is a spiral channel with a trapezoidal cross-section, which has better separation performance than a spiral channel with a rectangular cross-section. The second and third stages adopt symmetrical square serpentine channels with different rectangular cross-section widths for further separation and enrichment of sample cells reducing the outlet flow rate for easier downstream detection and analysis. The multistage channel can separate 5 μm and 15 μm particles with a separation efficiency of 92.37% and purity of 98.10% at a high inlet flow rate of 1.3 mL/min. Meanwhile, it can separate tumor cells (SW480, A549, and Caki-1) from massive red blood cells (RBCs) with a separation efficiency of >80%, separation purity of >90%, and a concentration fold of ~20. The proposed work is aimed at providing a high-throughput sample processing system that can be easily integrated with flowing sample detection methods for rapid CTC analysis.

Haimin Jiang, Brian P. Salmon, Timothy J. Gale et al.

Bradycardia is common in preterm infants and associated with a range of adverse outcomes, including end organ damage and developmental problems. This paper proposes a method to develop a generalised model to predict the onset of bradycardia in preterm infants by monitoring vital signs using artificial neural networks (ANN). Data used for network development was collected from a study conducted at the Royal Hobart Hospital involving 31 preterm infants, and comprising 3591 h of electrocardiogram (ECG) and respiratory motion recordings. ANNs with a multilayer perceptron architecture were employed with features from the ECG and respiratory signals as inputs. The ANN was trained to predict bradycardia within a pre-bradycardia period beginning 15 s prior to each bradycardic event. The ANN’s prediction capability was assessed using the area under the curve (AUC) of the receiver operating characteristic. Heart rate variability and respiration patterns were found to be indicative markers of an impending bradycardic event. When applied to new infants, the ANN using only ECG features achieved a mean AUC of 0.63, and the ANN using both respiratory features and ECG features achieved a mean AUC of 0.69. This approach has improved on previous attempts to predict bradycardia and should be further investigated.