Software Modules Research Articles

The Method of Measuring the Occupancy of the Radio Frequency Spectrum, Varying According to the Daily Cycle

Relevance. Management of the use of the radio frequency spectrum requires taking into account the actual occupancy of radio channels and frequency bands. However, the patterns of occupancy change underlying the International Telecommunication Union (ITU-R) Radiocommunication Sector documents do not fully meet the needs of practice. Some of the ITU-R recommendations are focused on estimating local occupancy for short time intervals; other recommendations involve measurements in stationary radio channels, although only a small part of real radio channels can be counted on to have the constant occupancy throughout the time axis. At the same time, the activities of many organizations, and therefore the resources they use, are subject to a daily cycle of activity, which allows us to recommend for consideration a model of occupancy change in accordance with the daily cycle. The aim of the work is to develop a methodology for collecting information and forming an estimate of the daily occupancy change for the analyzed radio channels. Methods used. The development of recommendations for the collection of data for occupancy monitoring is based on the practical approaches of radio monitoring services and classical methods of statistical analysis. Novelty. In this paper, a new model for changing the occupancy of radio frequency channels in accordance with the daily cycle is proposed for use, as well as a statistically justified method for measuring occupancy.Result. The proposed methodology allows us to obtain a practically oriented assessment of occupancy changes, which does not require replacing the fleet of equipment traditionally used by radio monitoring services; the necessary changes can be implemented with relatively simple software modification. The paper provides preliminary recommendations for ensuring the accuracy and reliability of measurements, based on a traditionally used mathematical apparatus, which involves limiting the relative measurement error. This entails the need for very long measurements for the most important low-occupied radio channels. So, it is necessary to look for alternative measurement accuracy requirements that would meet the real needs of radio monitoring services.Practical significance. The acceptance of the developed methodology will eliminate the currently existing contradiction between the theoretical provisions underlying the ITU recommendations and the practice of conducting radio-controlled measurements.

Repeatability of 3D MR fingerprinting during scanner software upgrades.

This study aims to quantify the repeatability of a 3D Magnetic Resonance Fingerprinting (MRF) research protocol in the context of a scanner software upgrade. All of MRI assumes consistent hardware performance and raw data pre-processing on the acquisition side. Software upgrades can affect hardware specifications and reconstruction chain parameters. Understanding how vendor-provided software upgrades vary MRF-derived T1 and T2 values is crucial for its application in different settings. Eight healthy volunteers were imaged with an in-house developed 3D MRF pulse sequence using a 3T scanner before and after a software upgrade (VA31A to VA50A, MAGNETOM Vida, Siemens Healthineers). Online MRF reconstruction using Singular Value Decomposition (SVD) timeseries compression and B1+ correction was performed. The study involved test-retest repeatability assessment and a comparison of pre- and post-upgrade data based on automatically extracted T1 and T2 values from MNI-152 Harvard-Oxford Subcortical Structural Atlas regions. Significant mismatches were found directly after the upgrade. However, after an information exchange with the vendor, the 3D-MRF sequence showed consistent repeatability in both intra-version test-retest scenarios and cross-version comparisons: 1.16 ± 3.18% variability in T1 and 0.54 ± 4.84% in T2 for intra-version tests, and 0.83 ± 3.68% (T1) and 0.05 ± 5.81% (T2) variability for cross-version comparisons. The study shows the reliable performance of 3D MRF protocols across software upgrades is possible, but it also highlights the importance of detailed evaluation and vendor collaboration in ensuring consistency. These findings support the application of MRF in longitudinal studies and emphasize the need for systematic assessments following hardware or software modifications.

Controller Area Network (CAN) Bus Transceiver with Authentication Support and Enhanced Rail Converters

This paper presents an advanced Controller Area Network (CAN) bus transceiver designed to enhance security using frame-level authentication with the concept of a nonphysical virtual auxiliary data channel. We describe the newly conceived transceiver security features and provide results concerning the design, implementation, fabrication and test of the transceiver to validate its functionality and robust operation in the presence of systemic error sources including Process, Voltage, and Temperature (PVT) variations. The virtual auxiliary channel integrates CAN frame authentication signatures into the primary data payload via phase modulation while also providing compatibility with existing CAN protocols, interoperability with non-enhanced systems and requiring no network or software modifications. Enhanced rail converters are designed to facilitate single-rail to dual-rail data conversion and vice versa, preserving phase information and minimizing phase errors across various nonideal effects such as frequency drift, Process, Voltage, and Temperature (PVT) variations, and cable phase mismatch. This ensures reliable data transmission and robust authentication in the presence of adversarial cyberattacks such as packet injection. The receiver recovers both the CAN frame data and the security signature, comparing the latter with an authorized signature to provide a real-time “GO/NO_GO” signal for verifying packet authenticity and without exceeding the CAN clock jitter specifications.

Deep learning assisted prediction on main factors influencing shear strength of sintered nano Ag-Al joints under high temperature aging

Bonding strength of sintered nano silver (Ag) joints has been an important index for evaluating the reliability of power module packages, which has been reported to be influenced by many factors. However, it is hard to evaluate and predict those factors affecting bonding strength. With the help of artificial intelligence (AI), the utilization of AI tools to assist in finding science solutions has become a mainstream consensus. In this paper, we will show how to evaluate and predict those sintered nano Ag-Al bonded joints bonding strength with deep learning (DL) methods. Firstly, a reliable extended dataset was obtained using the conditional formal condition table generation Induction Network (CTGAN) based on the die shear test dataset of sintered Ag-Al interface shear strength with four different metallization layers under different high-temperature aging time. Subsequently, four DL models were adopted to predict the shear strength of Ag-Al interface under different metallization layers to evaluate the interface bonding strength, all with high level of determination coefficient (R2, above 0.99) and classification accuracy (above 85%). Last but not least, factors influencing the shear strength of Ag-Al interface were analyzed and ranked by weight analysis and SHapley Additive exPlanations (SHAP) method. This research could provide a novel perspective on understanding those factors affecting the shear strength of sintered nano Ag interconnect layer in power devices.

THE RELATIONSHIPS AMONG GYMNASTS’ TRAINING AGE, BODY MASS INDEX, BALANCE CONTROL, AND GYMNASTICS PERFORMANCE

The aim of the study was the examination of the relationships among gymnasts’ training age, body mass index (BMI), balance control during the execution of handstand, standing scale forward, and stork standing in relevé position, and their performance in competition settings. Forty young competitive gymnasts (20 males; age: 12.20 ± 1.98 years, and 20 females; age: 12.33 ± 2.07 years, mean ± SD) participated in this study. A portable digital platform for posturography was used to measure maximal pressure, center of pressure (CoP) sway area, CoP linear distance displacement and CoP velocity. The resulting data were analyzed using an integrated software module (Foot Checker, version 4.0). The results confirm the reliability of the measurements. Strong positive correlations were found between gymnasts' performance in the gymnastics competition, and their training age and BMI, with relationships also identified between performance and variables related to balance control. Regression analysis revealed that gymnasts' training age, BMI, and balance control in performing the assessed gymnastics skills had predictive significance in determining their performance in the competition, taking into account differences between age groups. Despite the limitations of the study, the results represent a valuable contribution to the literature by expanding knowledge about predicting gymnastics performance in competition. Furthermore, the results provide evidence for the identification of talent in gymnasts, offer coaches insights to improve training efficiency, and provide recommendations for future research in this area.

ADDON FOR BLENDER3D. AUTOMATION OF THE OBJECT TEXTURING PROCESS

Abstract. Today, the use of 3D visualization technologies is one of the key directions in the field of information technologies. The 3D direction has become extremely popular in many fields, such as architecture, interior design, game industry, medicine, automotive and other fields. This method opens up new opportunities for perception and interpretation of information, adding it to a three-dimensional virtual space. The topic of the research work is the creation of a software module (addon) for the Blender3D program, which will provide the user with a library of ready-made materials, divided by categories. This addon has similar functionality to Substance Painter and Quixel Mixer, the main functions of which are to create and adjust materials and textures for imported ready-made 3D models. The addon has its own name "QuickShader" and will provide the user with 8 shaders and 35 PBR materials. Throughout the development of the project, the Waterfall life cycle model was used, stability and a clear structure were put first, which helped to efficiently work through each step of creating an addon for the Blender program. In the conclusion to the scientific work, it can also be noted that the development of a software addon for Blender3D, which includes a library of shader operators and PBR materials, will greatly facilitate the work of users when assigning textures to objects on the scene. A library of shader operators makes it easy to implement and customize shaders for light, glass, and some metals, giving you more control over the visual aspect of the scene. PBR materials provide realism due to the accurate representation of physical properties using Physically Based Rendering technologies. This addon gives users the ability to interact more effectively with procedural materials, providing a quick means to create realistic renders. This module automates the creation of materials by providing a list of prepared shaders and textures that can be applied to scene objects. The user will be provided with a set of ready-made shaders (glass, light material, metals) and PBR materials (wood, fabric, metals, and others), which can be applied with one button on the module panel.

Model study on transmission loss of the split-stream rushing exhaust muffler for diesel engine

Numerical simulation was carried out on the transmission loss of the split-stream rushing exhaust muffler, and the accuracy of the simulation method was verified through experiments. Taking the transmission loss as the response value, the experiment was designed by using Box-Behnken module of Design Expert software. A mathematical regression model of transmission loss with experiment factors was established by using the Box-Behnken experimental design scheme, the experiment factors include the diameter of the interior pipe, the shape of the rushing hole, the center distance of the rushing hole, the cone angle of the interior pipe as well as the number of rushing holes, and the mathematical regression model's significance was tested. The response curvatures of second order interaction to the transmission loss by different variables were obtained and the interaction relationships among variables were analyzed. The results showed that the diameter of the interior pipe and the center distance of the rushing hole are the main factors that affect the transmission loss. The transmission loss increases with the increase of the diameter of the interior pipe. When the diameter of the interior pipe is between 70 mm and 80 mm, the transmission loss firstly increases and then decreases with the center distance of the rushing hole changes from Smin to Smax. When the diameter of the interior pipe is between 80 mm and 90 mm, the transmission loss decreases with the center distance of the rushing hole changes from Smin to Smax. The effect of the rushing hole shape on transmission loss is not significant. The transmission loss increases with the increase of the number of rushing holes, but the increase of transmission loss is not significant with the number of rushing holes changes from 4 to 6 groups. Taking the transmission loss as the optimization index, the better experimental condition was obtained. Compared to the not optimized muffler of the sample engine, the average transmission loss of the optimized muffler is increased by 48.70 % when the frequency is 0-1000 Hz, the average insertion loss of the optimized muffler is increased by 7.4 %. At inlet air velocity of 40 m/s, the pressure loss is reduced by 56.8 %.

Refining software defect prediction through attentive neural models for code understanding

Identifying defects through manual software testing is a resource-intensive task in software development. To alleviate this, software defect prediction identifies code segments likely to contain faults using data-driven methods. Traditional techniques rely on static code metrics, which often fail to reflect the deeper syntactic and semantic features of the code. This paper introduces a novel framework that utilizes transformer-based networks with attention mechanisms to predict software defects. The framework encodes input vectors to develop meaningful representations of software modules. A bidirectional transformer encoder is employed to model programming languages, followed by fine-tuning with labeled data to detect defects. The performance of the framework is assessed through experiments across various software projects and compared against baseline techniques. Additionally, statistical hypothesis testing and an ablation study are performed to assess the impact of different parameter choices. The empirical findings indicate that the proposed approach can increase classification accuracy by an average of 15.93% and improve the F1 score by up to 44.26% compared to traditional methods.

SensorHUB – a Novel, Open-source Software Stack for Enhanced Accessibility and Secure Interoperability in IoT Project Management

Abstract. The Internet of Things (IoT) seeks to achieve seamless device connectivity and data sharing, thereby enhancing automation, efficiency, and insights in various fields of application. By delivering real-time data, IoT is essential for systems that aim to model and map the physical world to digital formats, such as digital twins or metaverses. In the recent years, there has been a surge in high-quality commercial IoT products available to various sectors. However, these solutions often come with high costs and proprietary interfaces, which hinder seamless interoperability. For users seeking cost-effective and flexible solutions, open-source software and international standards present viable alternatives. Nonetheless, despite technological progress, the adoption of open and standardized IoT software solutions is still predominantly seen among technology-affine groups or within research and development initiatives. We propose the sensorHUB, a novel IoT stack, which builds upon the Open Geospatial Consortium’s (OGC) data standard SensorThings API and enhances existing solutions towards more accessible, production-oriented solutions for diverse application domains and user groups. Key features include the provision of a new, state-of-the-art graphical user interface for managing data flows and the access to related software modules, and a secure and flexible user and access management.

Vision Systems for a UR5 Cobot on a Quality Control Robotic Station

This paper addresses the development of a vision system for the UR5 cobot and the corresponding operating algorithm of the robotic quality control station. The hardware–software architecture of the developed robotic station consisting of a UR5 cobot equipped with a web camera and a stationary industrial camera with a lighting system is presented. Image processing and analysis algorithms are described, the method of control and communication between the station components is discussed, and operating scenarios are presented as a single robotic station and as a part of the robotic line. Based on the results which were obtained, the level of measurement noise, accuracy, and repeatability of the developed vision system were estimated. A novel complete vision system architecture with hardware–software modules for the UR5 cobot quality control station is shown and discussed. The software part based on Python 3.12 language, OpenCV 4.7.0.68 libraries, and the PolyScope 1.8 environment incorporates modules for system calibration, image acquisition, preprocessing and image analysis (for objects’ location and geometric measurements) and for robotic cell communication and control. The hardware part of the UR5 cobot vision system is based on a PC with two independent and distinct cameras: one permanently affixed and the other mounted to the cobot’s flange. This innovative setup, combined with software architecture, broadens the scope of existing robotic quality control applications.

All-optical simultaneous OR and AND optical logic gates based on nonlinear photonic crystal ring resonator

Abstract An all-optical simultaneous OR and AND logic gates using the nonlinear Kerr effect and ring resonator based on a two-dimensional photonic crystal are proposed in this paper. The proposed structure has a resonant wavelength of 1551.3 nm and a power consumption (1 kW/μm2). The proposed structure is suitable for all-optical photonic integrations because of its simplicity and small size (23 μm x 30.4 μm). Moreover, the structure executes two logic operations without requiring an additional spare/control signal through a single structure, making fabrication easy. The total footprint of the photonic crystal ring resonator structure measures approximately 699 μm². A very high contrast ratio of 26.10 dB and 25.34 dB is obtained for the OR and AND logic gates, with response times equal to 2 ps and 0.67 ps, respectively. In addition, the calculated bit rates for OR and AND logic gates are approximately 0.5 and 1.5 Tbps, respectively. Using the Rsoft CAD commercial software, the FullWAVE and BandSOLVE module of the software is used for numerical and theoretical investigation of the structure.

Construction Jobsite Image Classification Using an Edge Computing Framework

Image classification is increasingly being utilized on construction sites to automate project monitoring, driven by advancements in reality-capture technologies and artificial intelligence (AI). Deploying real-time applications remains a challenge due to the limited computing resources available on-site, particularly on remote construction sites that have limited telecommunication support or access due to high signal attenuation within a structure. To address this issue, this research proposes an efficient edge-computing-enabled image classification framework for support of real-time construction AI applications. A lightweight binary image classifier was developed using MobileNet transfer learning, followed by a quantization process to reduce model size while maintaining accuracy. A complete edge computing hardware module, including components like Raspberry Pi, Edge TPU, and battery, was assembled, and a multimodal software module (incorporating visual, textual, and audio data) was integrated into the edge computing environment to enable an intelligent image classification system. Two practical case studies involving material classification and safety detection were deployed to demonstrate the effectiveness of the proposed framework. The results demonstrated the developed prototype successfully synchronized multimodal mechanisms and achieved zero latency in differentiating materials and identifying hazardous nails without any internet connectivity. Construction managers can leverage the developed prototype to facilitate centralized management efforts without compromising accuracy or extra investment in computing resources. This research paves the way for edge “intelligence” to be enabled for future construction job sites and promote real-time human-technology interactions without the need for high-speed internet.

Разработка DLP-модуля для защиты персональных данных в распределенной автоматизированной системе

The importance of personal data protection in automated systems is being considered. A study is provided on the development of a software module for protecting confidential information, including personal data, in a distributed automated system. The primary goal of the study: to create is to create software that prevents leaks of confidential information. The developed software module is designed to block the leakage of confidential information through network channels and removable media using a machine learning model with centralized security administrator management. The practical significance: the use of this module in organizations includes ensuring centralized information security management, reducing the risk of confidential data leaks, and supporting the investigation of security incidents. The research can be used as a temporary measure during the period of updating and adapting the system to new realities until a full-fledged protection system is achieved.

Structure of software and hardware module for research of DC electrical machines. Part 1

The structure of a hardware and software complex for the study of DC electric machines and a mathematical model of its electromechanical part taking into account the influence of temperature on the resistance of the armature winding have been developed. The hardware and software complex is implemented on the Arduino Uno board. A distinctive feature of which is the modular structure, which allows conducting research on DC electric machines in various operating modes (start-up, armature speed control, reversing, braking). In addition, it is possible to implement various laws of changing the load moment. For this purpose, the hardware and software module include the studied and load DC electric machines, which are mechanically connected to each other by means of a coupling and operate in motor and generator modes, respectively. The proposed model makes it possible to describe electromagnetic processes in DC electric machines taking into account the influence of temperature on the resistance of the armature winding, as well as overheating of individual parts of the electric machine. The proposed hardware and software module can find practical application in research laboratories in the study of DC electric machines in various operating modes.

Implementation of an autonomous mobile platform for agricultural tasks in corridor-like environments

AbstractThe role of autonomous vehicles (AVs) in assisting people is recognised and, therefore, is in constant development in numerous fields. Specifically, the ability of an autonomous vehicle (AV) to alleviate global stressors, such as the increased potential for food shortages and the decline in available workers for labor-intensive tasks. An area where the development of AVs are particularly prevalent is in agriculture. However, the few AVs being used in agriculture are often custom-built for specific purposes and require long development time as a result. This article aims to build and evaluate a versatile architecture for a mobile platform that is implemented using off-the-shelf components so that it can be transferred to any agricultural vehicle, thus reducing the development time. The research has involved investigating and incorporating various sensors, and also developing a common software module to perform the localisation, navigation and mapping particularly suited for corridor crop agricultural environments. This architecture has been integrated and implemented on a Yamaha golf cart, integrating it with sensors and electronics to allow a Robotic Operating System (ROS) framework to gather information and control the vehicle. As the architecture is modular in nature, it can be transferred to different customised platforms. To determine the efficacy of the mobile platform, it has undergone evaluation in simulation and in the field. The evaluation demonstrates that both mapping and navigation have satisfactory results, and the mobile platform remains within 5 mm of the specified distance when aiming to follow the row in a vineyard. The results from these experiments demonstrate the ability of the mobile platform to successfully transform a Yamaha golf cart into an autonomous agricultural vehicle.

Optimization of atomization performance of external mixing air atomizing nozzle based on response surface agent model

Based on the finding that the atomization performance of the nozzle is affected by its structural parameters, a combination of finite element analysis and structural optimization calculations is used. Finite element analysis was performed through the VOF (Volume of Fluid) module of Fluent software to determine the structural parameters affecting the performance of the atomizing nozzle. The liquid cyclone tank inclination, the length of the flat section at the gas outlet, and the mixing chamber outlet diameter were used as optimization factors. The atomization cone angle and fuel atomization circumferential distribution uniformity index were used as the evaluation indexes of atomization performance. An orthogonal experimental design was carried out based on the above. Proxy model for atomization cone angle and fuel atomization circumferential distribution uniformity index based on response surface method. The optimal structure of the nozzle was obtained by optimization calculation of the agent model by genetic algorithm. The results show that the atomization performance is optimal when the inclination angle of the liquid rotating tank is 42.9, the length of the flat section at the gas outlet is 3.3, and the diameter of the mixing chamber outlet is 5.0. The atomization cone angle increased by 23.07 % compared with the original model, and the fuel atomization circumferential distribution uniformity index decreased by 45.06 %. A new solution for the design of externally mixed air atomizing nozzles is provided.

Creation of self-aligning multisatellite planetary gears

In this study, we aim to identify shortcomings in the operation of multisatellite planetary gearboxes and to justify improved designs of planetary self-aligning mechanisms, which allow torque to be transmitted through all installed satellites. To that end, we studied a domestic planetary three-satellite MPZ gearbox installed on a magnetic separator, designed for wet separation of strongly magnetic ores and materials into magnetic and non-magnetic products, and a planetary gearbox of a special structure. 3D models of the classical three-satellite and single-sliding self-aligning gearboxes were constructed in the 3D module of the T-Flex CAD software. The performance of the mechanisms was evaluated by structural analysis and Chebyshev’s mobility formula. The constructed 3D models were used to study the engagement process of the classical three-satellite and single-sliding self-aligning gearbox. The latter is distinguished by the presence of two levers, which are introduced additionally to three satellites. During the research, the lateral clearance between the pairs of satellite teeth and center wheels was accepted according to GOST 1643–81. The conducted analysis of contacts at rotation of the central driving wheel by 30°, 110°, 200°, and 310° established further designing of the applied planetary gears to be inexpedient due to impossibility of realization of power transfer simultaneously through all satellites. The main disadvantage of the operation of multisatellite gearboxes was found to be the requirement for the side clearance selection, which should ensure the operability of the transmission at the moment of motion transfer. When designing multi-satellite single-slide selfaligning planetary mechanisms, additional levers should be introduced into the structure, the number of which should be equal to the number of satellites. Hence, the use of self-aligning planetary gears makes it possible to reduce the dimensions due to the uniform distribution of the transmitted torque, since the calculated value of the torque can be reduced by the number of satellites. This allows the gears to be adapted to the working loading conditions, which significantly improves the performance of the entire machine or unit.

Anesthesia-Specific Software Module for Voluntary Adverse Event Reporting

Objectives Hospital staff are expected to report adverse events to safety leaders and risk managers. At our institution, staff report adverse events via an incident reporting software system, known as “RL.” These “RL reports” are kept separate from patient medical records. Within the Anesthesiology Department, we noted low numbers of RL reports relative to known adverse events. Anesthesiology-related events were scattered within the RL software and therefore difficult to find. We hypothesized that compiling these events in one location would increase reporting rates and allow for deeper analysis of filed adverse events. Methods We created an Anesthesia-specific RL software module, which included all anesthesia-related adverse events in one location. Additionally, we tracked the impact on RL reporting of two other quality improvement initiatives, including an intradepartmental quality assurance form, implemented during the study period. Results The Anesthesia RL software module led to a 3.2-fold increase (P < 0.001) in the monthly average of filed RL reports. The increase was even greater (11.1-fold, P < 0.001) when excluding the most prevalent category of RL reports (Controlled Substance Discrepancies). The intradepartmental quality assurance form had minimal impact on filed RL reports. “Controlled Substance Discrepancies,” “Other,” and “Equipment issue” were the most common event types. Most events were classified as constituting no harm to the patient. Conclusions Creating a specialty-specific RL software module led to increased RL reports, even when accounting for other implemented quality improvement initiatives, and allowed for deeper analysis of the filed reports. Our findings may be replicated for other specialties.

GreenHopper: The Danish spearhead towards autonomous waterborne mobility

Abstract GreenHopper is the first Danish zero-emission ferry developed as a test platform for autonomous waterborne navigation technologies. The paper presents technology development within the innovation project ShippingLab Autonomy, which led to the commissioning of GreenHopper at Limfjorden (DK) in December 2022. The technology research resulted in a holistic system architecture for surface vessel autonomy, based on distribution of functionality and responsibility on software modules, similar to the structure observed in the International Maritime Organization (IMO) Seafarers Training Certification and Watch-keeping (STCW) regulatory framework. The paper shows how this approach results in an architecture that supports safe behaviours of individual modules and of autonomous navigation at a system level. The paper presents the individual modules, specific features and benefits. Elements of the regulatory framework are highlighted to poise technology approval by maritime authorities. The paper reflects on lessons learned, discusses continued technology validation in dedicated operational scenarios.

The Universal Module for Integration of an Intelligent Assistant into iOS Applications

Investigated current implementations of the integration of intelligent assistants into mobile applications. Identified key disadvantages of existing implementations and formed the criteria for a universal intelligent assistant. Developed a proprietary software module for integrating an intelligent assistant into iOS application, which provides autonomy, minimal resource requirements, and simplifies the development process. Created a photo editor application to test the operation of the software module. The test results were presented and further development prospects were described.