Generating fit-for-purpose CAD models from complex assemblies is time consuming for analysts. Tedious tasks include to identify and isolate the components of interest for the analysis, remove duplicate components, or correct inconsistent components’ interfaces are common for large assemblies during the product development process. In this paper a new approach to help engineers analyse the consistency of CAD assembly models is proposed. The method utilises a tensor factorisation technique developed for relational machine learning and applies it on B-Rep topological and geometrical relations. The generated decomposition is used to identify which entities in the assembly are similar (within a threshold) to a selected input entity. The factorisation model regards globally all input relationships, e.g. the connections between components, to identify similar entities based on their relationships in the relational domain. It is shown that a hierarchical clustering method can group entities based on the similarities of their attributes and relationships.

Emily J. Patel, Liam M. Fraser, Aiden C. MacLeod, Olivia R. Wallace. “Tensor-Based Analysis of CAD Assembly Similarities.” Computer Engineering, vol. 15, no. 6, pp. 1-23, 2026.

Copy Citation

The aim. Estimation of ST2 plasma level in patients with acute myocardial infarction without ST elevation (NSTEMI) and its relationship with different clinical characteristics. Materials and methods. 165 patients aged from 35 to 79 (average of 60.7±0.8 years) with various forms of coronary artery disease (CAD) with and without arterial hypertension were examined. The variability of plasma ST2 level in different forms of CAD and in NSTEMI group was analyzed depending on gender-age and clinical characteristics and features of the disease course. Results: The results of the present investigation were that the ST2 level in the main cohort was in range from 5.5 to 233.9 (in the middle – 49.8±3.5 ng/ml (median indicator – 34.7 and the interquartile range – 21.9 and 59.1 respectively). Significantly higher ST2 levels were found in patients with NSTEMI, unlike the comparison group, in the median analysis (35.9 vs. 27.7 ng/ml, p=0.047) and no statistical differences were observed in the mean values. In patients with NSTEMI, a certain association of ST2 level in plasma with the MI course was detected. A higher level of neurohormone is registered with anterior unlike posterior ECG localization of MI; at high unlike moderate risk on the GRACE scale; when complicated unlike the uncomplicated course of MI; in the case of acute HF and cardiac arrhythmias unlike patients with the absence of these manifestations in the acute period of MI. Conclusions. High variability of ST2 level in plasma was demonstrated in patients with NSTEMI on the first day after destabilization (minimum and maximum values – 12.7 and 233.9 respectively, median – 35.9 and interquartile range – 25.9 and 55.7 ng/ml). It is shown that significantly higher ST2 level in plasma is determined in patients with acute MI regardless of its variant among different clinical forms of CAD. It is found that significantly higher level of ST2 in patients with NSTEMI is recorded in the case of concomitant HTN and type 2 diabetes, with smoking and heavy cardiovascular heredity. Proved influence of the character of MI course on the level of ST2 in plasma, significantly higher level of neurohormone was determined with anterior localization of MI, high risk on the GRACE scale (≥140 points), complicated course of MI, development of cardiac arrhythmias and HF in the acute period of MI.

Elevation: Insights into Clinical Heterogeneity. “Plasma Biomarkers in Acute Myocardial Infarction without ST Elevation: Insights into Clinical Heterogeneity .” Computer Engineering, vol. 15, no. 6, pp. 24-32, 2026.

Copy Citation

A method for determining the contours of objects on complexly structured color images based on the ant colony optimization algorithm is proposed. The method for determining the contours of objects of interest in complexly structured color images based on the ant colony optimization algorithm, unlike the known ones, provides for the following. Color channels are highlighted. In each color channel, a brightness channel is allocated. The contours of objects of interest are determined by the method based on the ant colony optimization algorithm. At the end, the transition back to the original color model (the combination of color channels) is carried out. A typical complex structured color image is processed to determine the contours of objects using the ant colony optimization algorithm. The image is presented in the RGB color space. It is established that objects of interest can be determined on the resulting image. At the same time, the presence of a large number of “garbage” objects on the resulting image is noted. This is a disadvantage of the developed method. A visual comparison of the application of the developed method and the known methods for determining the contours of objects is carried out. It is established that the developed method improves the accuracy of determining the contours of objects. Errors of the first and second kind are chosen as quantitative indicators of the accuracy of determining the contours of objects in a typical complex structured color image. Errors of the first and second kind are determined by the criterion of maximum likelihood, which follows from the generalized criterion of minimum average risk. The errors of the first and second kind are estimated when determining the contours of objects in a typical complex structured color image using known methods and the developed method. The well-known methods are the Canny, k-means (k=2), k-means (k=3), Random forest methods. It is established that when using the developed method based on the ant colony optimization algorithm, the errors in determining the contours of objects are reduced on average by 5–13 %.

Optimization. “Object Contour Detection in Complex Color Images Using Ant Colony Optimization.” Computer Engineering, vol. 15, no. 6, pp. 33-47, 2026.

Copy Citation

The aim of the article is development of a technique for visualizing information for use in multimedia applications. In this study, to visualize information, it is proposed first to compile a list of key terms of the subject area and create data tables. Based on the structuring of fragments of the subject area, a visual display of key terms in the form of pictograms, a visual display of key terms in the form of images, and a visual display of data tables are performed. The types of visual structures that should be used to visualize information for further use in multimedia applications are considered. The analysis of existing visual structures in desktop publishing systems and word processors is performed. To build a mechanism for visualizing information about the task as a presentation, a multimedia application is developed using Microsoft Visual Studio software, the C# programming language by using the Windows Forms application programming interface. An algorithm is proposed for separating pieces of information text that have key terms. Tabular data was visualized using the “parametric ruler” metaphorical visualization method, based on the metaphor of a slide rule. The use of the parametric ruler method on the example of data visualization for the font design of children’s publications is proposed. Interaction of using the method is ensured due to the fact that the user will enter the size of the size that interests for it and will see the ratio of the values of other parameters. The practical result of the work is the creation of a multimedia application “Visualization of Publishing Standards” for the visualization of information for the font design of publications for children. The result of the software implementation is the finished multimedia applications, which, according to the standardization visualization technique in terms of prepress preparation of publications, is the final product of the third stage of the presentation of the visual form.

Dr. Ananya Sharma. “Enhancing Multimedia Experience through Advanced Information Visualization Techniques.” Computer Engineering, vol. 15, no. 6, pp. 48-64, 2026.

Copy Citation

Recently, many uses of artificial intelligence have appeared in the commercial field. Artificial intelligence allows computers to analyze very large amounts of information and data, reach logical conclusions on many important topics, and make difficult decisions, this will help consumers and businesses make better decisions to improve their lives, and it will also help startups and small companies achieve great long-term success. Currency exchange rates are important matters for both governments, companies, banks and consumers. The decision tree is one of the most widely artificial intelligence tools used in data mining. With the development of this field the decision tree and Gradient boosting decision tree are used to predicate through constructed intelligent predictive system based on it. These algorithms have been used in many stock market forecasting systems based on global market data. The Iraqi dinar exchange rates for the US dollar are affected in local markets, depending on the exchange rate of the Central Bank of Iraq and the features of that auction. The proposed system is used to predict the dollar exchange rates in the Iraq markets Depending on the daily auction data of the Central Bank of Iraq (CBI). The decision tree and Gradient boosting decision tree was trained and testing using dataset of three-year issued by the CBI and compare the performance of both algorithms and find the correlation between the data. (Runtime, accuracy and correlation) criteria are adopted to select the best methods. In system, the characteristic of artificial intelligence have been integrated with the characteristic of data mining to solve problems facing organization to use available data for decision making and multi-source data linking, to provide a unified and integrated view of organization data.

Amal A. Al-Sheikh. “Comparing the Performance of Decision Trees and Gradient Boosting Decision Trees in Exchange Rate Forecasting.” Computer Engineering, vol. 15, no. 6, pp. 65-71, 2026.

Copy Citation

This paper presents authors analytical view on social impacts as targeted advertisement into the network environment using Omori tectonic theory for description the processes of audience response evolution. This could be extremely important and useful in the modern world to realize desirable e-Gov informational policy in the circumstances of hybrid treats emergence that is especially relevant for the informational space and reaching a cyber-supremacy. Some mathematical and algorithmic basics were contributed for narrative description of information and communications technologies (ICT) architectural deployment could be used for outer regulation of audience response character by Social Media Marketing (SMM) principles. That could be performed by controlled distribution of specified digital content that contains respective key phrases, for example social advertisements and analyzing respective feed-backs. Some results of the empiric study of live audience response dependence on controlled impacts are discussed. Election processes data and recent media recordings for preliminary proof of the contributed concept feasibility have been analyzed. There were shown using gathered empiric data sets, that the extent of impacts to targeted audience response intensity could be the subject of outer regulation. The index has been contributed for assessment the efficiency of the impact’s propagation inside the audience by calculation of row correlation of keyword occurrence and audience response intensity. The approaches suggested in the article can be useful both for building effective interactive systems of state-society interaction and for detecting manipulative traits when influencing a specific audience.

Anastasia Petrov, Katarzyna Szymańska. “Exploring the Paradigm of ICT Platforms in Social Media Marketing: A Tectonic Shift in Deployment Strategies.” Computer Engineering, vol. 15, no. 6, pp. 72-88, 2026.

Copy Citation

: This tutorial paper focuses on the variants of the bottleneck problem taking an information theoretic perspective and discusses practical methods to solve it, as well as its connection to coding and learning aspects. The intimate connections of this setting to remote source-coding under logarithmic loss distortion measure, information combining, common reconstruction, the Wyner– Ahlswede–Korner problem, the efficiency of investment information, as well as, generalization, variational inference, representation learning, autoencoders, and others are highlighted. We discuss its extension to the distributed information bottleneck problem with emphasis on the Gaussian model and highlight the basic connections to the uplink Cloud Radio Access Networks (CRAN) with oblivious processing. For this model, the optimal trade-offs between relevance (i.e., information) and complexity (i.e., rates) in the discrete and vector Gaussian frameworks is determined. In the concluding outlook, some interesting problems are mentioned such as the characterization of the optimal inputs (“features”) distributions under power limitations maximizing the “relevance” for the Gaussian information bottleneck, under “complexity” constraints.

Olivia R. Thompson and Julian M. Reyes. “The Information Bottleneck Problem: A Theoretical and Computational Analysis.” Computer Engineering, vol. 15, no. 6, pp. 89-128, 2026.

Copy Citation

The present study is carried out for a steam turbine shaft. Analysis of stresses and strain for mechanical load on a High pressure steam turbine shaft is done by using FEM analysis. A steam turbine rotor is considered. It carries wheels, bearing journals, and other parts connected to it. The function of steam turbine shaft is to transmit the power to driven mechanism. The blades are grooved to shaft at each stage. The mechanical forces on the steam turbine due the velocity of the steam and various mountings on the steam are studied. The tangential, axial and centrifugal forces on the steam turbine are calculated. The material 30CrMoVsteel is used for the shaft. The properties of material are applied on the software model. Then suitable boundary conditions are applied on the CAD model of shaft and analysis is carried out by using FEM software ANSYS.

Arjun Vijay, Priya Nayak. “Investigation of Mechanical Stress and Strain in High-Pressure Steam Turbines under Variable Loading Conditions.” Computer Engineering, vol. 15, no. 6, pp. 129-137, 2026.

Copy Citation

In recent years, in the oil and gas industry of Azerbaijan, the use of electric submersible pumps (SEP) as one of the effective way to increase the level of production of well products. Currently, electric centrifugal pumping units (ECPU) are widely used both on land and in offshore fields. Currently, a total of about 15 % of SOCAR’s oil wells are produced using electric submersible pumping units. ECPU effectiveness is largely determined by both the period of their operation and the frequency of repair and restoration work. It is established that the use of ECPUs contributes to an increase in the service life of equipment and the effectiveness of a mechanized method of oil production. To assess the benefits of the latter, the most important factor is the inter-repair period (Tir) of the equipment. Existing methods for determining the inter-repair period of oilfield equipment are accompanied by large errors, which significantly reduce their reliability. In this regard, the article is tasked with developing a more practical and reliable method for determining the inter-repair period, where the point of change in the nature of the failure rate is adopted as the determining parameter.

Farkhad Rzaev Mammadov. “Optimization Strategies for Electric Submersible Pump Unit Maintenance.” Computer Engineering, vol. 15, no. 6, pp. 138-146, 2026.

Copy Citation

Inverse problems play a significant role in economic analysis and decision-making, as they enable the determination of input factors required to achieve a desired outcome. Unlike direct problems, which focus on calculating results from known causes, inverse problems seek to identify the causes that lead to a specified effect. This study examines the application of inverse computing methods for solving economic inverse problems using expert information. The proposed approach incorporates additional knowledge, including the relative importance of variables and the direction of their expected changes, to determine the required values of function arguments corresponding to a target result. The relationships among economic indicators are represented through a hierarchical tree structure, allowing complex dependencies to be analyzed systematically. A profitability model, where profitability is defined as the ratio of profit to cost, is used to illustrate the implementation of direct and inverse calculations. The results demonstrate that the inverse computing apparatus provides an effective mechanism for identifying control actions and supporting managerial decision- making. The proposed methodology enhances the capabilities of decision support systems by enabling the formulation of strategies required to achieve predetermined economic objectives and improve organizational performance.

Anastasiya Fedorova and Viktor Kuznetsov. “Investigating Algorithmic Approaches for Inverse Problem Resolution in Economic Analysis under Constraining Conditions.” Computer Engineering, vol. 15, no. 6, pp. 147-156, 2026.

Copy Citation