Software Modules Research Articles

Transforming Service Management: The Implementation of AMC Software Solutions in Modernizing Product Servicing

In today's dynamic business environment, organizations are compelled to adapt swiftly to stay competitive. Smart Information Management has emerged as a crucial strategy for achieving agility and efficiency. This paper introduces the concept of the AMC Management System, a comprehensive software solution designed to optimize product servicing within the framework of UPRNNS. The AMC system aims to automate and streamline complaint registration, resolution, and data management processes, thereby enhancing customer satisfaction and operational efficiency. This paper explores the objectives, challenges, proposed digital solution, business needs, scope, benefits, and project analysis of the AMC Management project. Additionally, it outlines the software requirements, entities involved, modules, and future scope of the project, highlighting the potential for integrating advanced technologies such as artificial intelligence, machine learning, and the Internet of Things to further enhance service delivery and customer engagement. Keywords— Smart Information Management, AMC Management System, Product Servicing, Automation, Customer Satisfaction, Digital Solution, Future Scope.

Analytical and Experimental Behaviour of GFRP-Reinforced Concrete Columns under Fire Loading

Fire engineering endeavours to mitigate injury or the loss of life in the event of a fire. This is achieved primarily through fire prevention, containment, and extinguishment measures. Should prevention fail, the structural integrity of buildings, coupled with effective evacuation strategies, becomes paramount. While glass fibre-reinforced polymer (GFRP) materials have demonstrated efficacy in reinforcing concrete elements, their performance under fire conditions, notably in comparison to steel, necessitates a deeper understanding for structural applications. This study experimentally and numerically investigates the fire performance of GFRP-reinforced concrete (RC) columns subjected to only fire load without additional external loads. The research aims to ascertain the fire resistance based on the thickness of the concrete coating and the ultimate tensile strength of GFRP rebars after 90 min of fire exposure. Four GFRP-RC columns were subjected to a standardized fire curve on all sides in the experimental program. In the analytical program, a theoretical model was developed using the heat transfer module of the COMSOL software. The results of both analyses were very close, indicating the reliability of the procedure used. Based on the findings, recommendations regarding the fire resistance of GFRP-RC columns were formulated for structural applications. Results from this research provide the civil engineering community with data that will help them continue using FRP materials as internal reinforcement for concrete.

A clustering-based resampling technique with cluster structure analysis for software defect detection in imbalanced datasets

Software defect detection focuses on the automatic identification of flaws in software modules. Given the great importance of the problem, numerous researchers have introduced a rich collection of deep learning approaches to confront it. However, the datasets that are used to train the proposed classifiers are in most cases highly imbalanced, leading to models that cannot learn the minority classes effectively, while being biased towards the majority class. The state-of-the-art solutions either overlook the issue of data imbalance, or they confront it insufficiently by ignoring the existence of outliers and the local properties of the classes' distributions. In this work we introduce CBR, a Clustering-Based Resampling technique for mitigating the problem of class imbalance in software defect detection tasks. The proposed method initially employs a quite simple heuristic to determine the maximum distance threshold between two clusters. Then, it uses this threshold to apply hierarchical clustering with the aim of grouping together similar samples. CBR considers the singleton clusters as outliers, and discards the ones originating from the majority class. The algorithm subsequently organizes the clusters into sub-clusters than contain samples from the same class and determines which sub-clusters should participate in the oversampling process. In this way, CBR produces samples of improved quality and variance. We evaluated the performance of CBR against 9 baseline and state-of-the-art techniques by using 27 datasets and a Multilayer Perceptron classifier. The results demonstrate the superiority of CBR in terms of Balanced Accuracy and Precision scores.

Detection of quantitative trait nucleotides (QTNs) and QTN-by-environment and QTN-by-QTN interactions for cotton early-maturity traits using the 3VmrMLM method

Early maturity is among the most important and complex agronomic traits of upland cotton (Gossypium hirsutum). Using the recently established 3VmrMLM method, a genome-wide association study was conducted, focusing on three primary early-maturity traits: growth period (GP), the first fruiting branch node (FFBN), and height of the first fruiting branch node (HFFBN). As a result, 45, 37, and 1 quantitative trait nucleotides (QTNs) for GP, 51, 28, and 0 QTNs for FFBN, and 84, 39, and 3 QTNs for HFFBN were detected by the “Single_env”, “Multi_env”, and “Epistasis” modules of IIIVmrMLM software, respectively. Of these QTNs, two for GP, two for FFBN, and three for HFFBN were simultaneously detected in at least three datasets or by at least three modules. The three genes, GH_D08G2175, GH_D08G2201, and GH_D09G2513, associated with the stable QTNs were further verified by qRT-PCR and haplotype analysis. Fourteen QTN-by-environment interactions (QEIs), comprising two for GP, seven for FFBN, and five for HFFBN, were detected, of which nine QEIs exhibited significant phenotypic differences between different genotypes under various environments. Three of the nine QEIs were respectively located within the genes GH_D12G1405, GH_D05G2088, and GH_D11G1027, which are likely to interact with environments and thus affect early maturity. Altogether 21 QTN-by-QTN interactions (QQIs), comprising 5 for GP and 16 for HFFBN, representing interactions between various effects were detected. Ten protein–protein interactions involving 6 QQIs and 10 gene pairs were predicted. The findings offer fresh perspectives on the genes underlying early maturity, advancing the prospects for molecular design breeding in cotton.

Efficient Block Designs for Mixed Level Factorial Microarray Experiments based on Baseline Parameterization

A procedure of obtaining efficient block designs in block size 2 for n-factor mixed level factorial microarray experiments based on baseline parameterization has been given. A software module has been developed using C# programming language with ASP.NET platform for generation of efficient block designs in block size 2 for s1 × s2 ×× sn factorial experiments in v −1 arrays, where j s denotes the number of levels of jth factor and n denotes the number of factors and 1 n j j v s = = Π , the total number of treatment combinations. For n = 2, the software developed can also generate efficient block designs for 1 2 v −1≤ b ≤ ( v −1) + ( s −1)( s −1) , where b is the number of arrays.

Predictive Analytics for Motorcycle Theft Detection and Recovery

Transportation is an integral component of our daily lives, and it is becoming increasingly common for people in the Philippines to rely on vehicles, such as motorcycles, as their primary mode of transportation. The prevalence of motorcycle theft has risen concurrently with the growing number of motorcycle users over the years. To address this issue, a system has been devised for the effective prevention and retrieval of stolen motorcycles in a timely and efficient manner. The user of this system is alerted through an alert notification when the motorcycle has been moved over a considerable distance or has been stolen. Additionally, the user can view the current location of the motorcycle, turn off the engine, and capture an image of the thief. The system is composed of two parts: hardware and software modules. The hardware component includes a micro-controller, GSM, GPS, and a camera. The motorcycle serves as the primary controller of the entire system and is also responsible for its operation. According to the usability and functionality evaluation conducted, it was discovered that most users strongly agreed on the usefulness of the system.

A new binary chaos-based metaheuristic algorithm for software defect prediction

Software defect prediction is a critical challenge within software engineering aimed at enhancing software quality by proactively identifying potential defects. This approach involves selecting defect-prone modules ahead of the testing phase, thereby reducing testing time and costs. Machine learning methods provide developers with valuable models for categorising faulty software modules. However, the challenge arises from the numerous elements present in the training dataset, which frequently reduce the accuracy and precision of classification. Addressing this, selecting effective features for classification from the dataset becomes an NP-hard problem, often tackled using metaheuristic algorithms. This study introduces a novel approach, the Binary Chaos-based Olympiad Optimisation Algorithm, specifically designed to select the most impactful features from the training dataset. By selecting these influential features for classification, the precision and accuracy of software module classifiers can be notably improved. The study's primary contributions involve devising a binary variant of the chaos-based Olympiad optimisation algorithm to meticulously select effective features and construct an efficient classification model for identifying faulty software modules. Five real-world and standard datasets were utilised across both the training and testing phases of the classifier to evaluate the proposed method's effectiveness. The findings highlight that among the 21 features within the training datasets, specific metrics such as basic complexity, the sum of operators and operands, lines of code, quantity of lines containing code and comments, and the sum of operands have the most significant influence on software defect prediction. This research underscores the combined effectiveness of the proposed method and machine learning algorithms, significantly boosting accuracy (91.13%), precision (92.74%), recall (97.61%), and F1 score (94.26%) in software defect prediction.

Rand-Index Target Projective Gradient Deep Belief Network for Software Fault Prediction

Predicting defective software modules before testing is a valuable operation that reduces time and cost of software testing. Source code fault prediction plays a vital role in improving software quality that effectively assists in optimization testing resource allocation. Several machine learning and ensemble learning techniques has been extensively evolved over the recent few years to predict defect at an early stage. These techniques made predictions based on historical defect data, the software metrics. Nevertheless, the time efficient and accurate fault predictions are the major challenging tasks that yet have to be addressed. In order to ensure accurate software fault prediction, a method called Rand-Index Target Projective Gradient Deep Belief Network (RTPGDBN) is designed. The proposed RTPGDBN method comprises of three processes namely acquiring JAVA packages, software metric selection and classification. First, the number of JAVA packages is used as input from the dataset. Second with the JAVA packages obtained as input, Rand similarity indexive target projection function is applied for selecting the most significant software metrics in order to minimize time complexity of fault prediction. Third, with the selected metrics, classification is performed using Tversky Gradient Deep Belief neural network. Also, gradient descent function is applied to minimize classification error, therefore ensuring accurate software fault classification results obtained at the output layer. Experimental setup of proposed RPGDDBN and existing methods are implemented in Java language and the dataset collected from smell prediction replication package. Performance analysis is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity and space complexity. Through extensive experiments on repository data, experimental results indicate that our RPGDDBN method outperforms two state-of-the-art defect detection methods in terms of different performance metrics.

Integration of Physical Reality Objects with Their 3D Models Visualized in Virtual Environment Systems

The paper describes methods and approaches for integrating, from the user's point of view, three-dimensional virtual models visible to them in a virtual reality headset, and their physical prototypes. This allows for the addition of some important elements of physical reality to the virtual environment, such as tactile and muscle-motor sensations. Developed solutions are based on the use of wireless HTC Vive trackers, which determine their position and orientation in space and have the ability to be attached to various objects in the real world. An original approach to building a tracking system from several controllers of such type with one anchor element selection is proposed, as well as new methods for real-time integration of physical reality objects with their virtual models by means of functional control schemes with blocks for the Vive trackers. Software modules were created based on developed methods and approaches. Approbation of them was carried out in virtual environment system VirSim and showed adequacy and effectiveness of proposed solutions when using in virtual environment systems and training complexes.

Static Load and Seismic Finite Element Analysis of DN1000 Large-Diameter Three-Pipe Gantry Hanger

Taking DN1000 large-diameter three-pipe and its gantry hanger as the research object, the finite element model was established by using beam element and solid element. The static load and seismic performance analysis of DN1000 three-pipe gantry hanger is carried out based on the spectral analysis function module of ANSYS software. The strength and stiffness of the hanger were seismically evaluated according to ASME AG-1 code. The results show that the use of H-beam steel (HW250) as the column and beam of the hanger meets the requirements of the seismic calibration, with a strength safety margin of more than 50% and a stiffness safety margin of more than 80%. Under the combination of static load and seismic load, the strength and stiffness also meet the requirements. This method has certain reference value for the seismic design and evaluation of the integrated hanger for large-diameter electromechanical pipelines.

Integrated heat dissipation mechanism design of electronic equipment cabinet based on flow and sound analysis

The electronic equipment cabinet is the main bearing platform of radar back equipment, normally using a forced convection cooling form. With the continuous increase of radar function and processing capacity, the total heat consumption of electronic equipment is getting higher and higher, and the fan speed is constantly increasing. Besides the noise of electronic equipment cabinet shows a trend of gradually increasing. To reduce cabinet noise from the source, this paper presents three structural forms of integrated heat dissipation mechanism, and uses FloEFD fluid heat transfer analysis software and COMSOL acoustic module to analyze the cabinet flow field and the cabinet sound field respectively. By comparing the cabinet noise characteristics under different structural forms, the analysis results show that the noise reduction effect of bilateral air duct structure is best.

Интерактивная геоинформационная система динамической визуализации характеристик аврорального овала на основе паттернов компонентно-ориентированного программирования

The practical need for operational monitoring of the position dynamics of the auroral oval is due to the negative technospheric manifestations of space weather effects observed in this spatial region. However, the well-known software tools for modeling the auroral oval solve this problem inefficiently from the point of view of informativeness and ergonomics. The paper proposes an approach to dynamic visualization of the characteristics of the auroral oval, which is available at the program level in the form of a traditional web application with the ability to render visual elements in the browser, as well as in the format of a standalone service like RESTful-API. The developed solution provides visualization of the following parameters: the probability of observing the glow of the upper layers of the atmosphere with the naked eye, the electric and magnetic potentials of the field in the region of the northern auroral belt, as well as various types of auroral precipitation. It is assumed that the proposed approach will make it possible to significantly increase the efficiency of the study of parameters in the auroral oval region by specialists and scientists in the relevant fields. At the same time, the high internal and low external connectivity of the developed software modules allow them to be integrated into third-party applications of various profiles and purposes.

Thermal management system for cell-biology experimental setup studying calcium signalling in microgravity

A novel hardware featuring specific LED arrays shall be developed to investigate free calcium in biological cells exposed to microgravity conditions. The temperature-sensitive samples require a precise and reliable temperature control system that can operate without electricity. In this paper, we assess the effectiveness of a passive temperature control system based on phase change material. Two extreme operation scenarios are investigated simulatively with the software COMSOL 6.1 for correct dimensioning and material selection. The simulation results of the first operation scenario show that the required temperature range for mammalian cells can be maintained during a power interruption of two hours. The simulation results of the second operation scenario show that excess heat generated by the LED arrays is effectively evacuated with a phase change material-based thermal management system. The physics software modules “heat transfer in solids and fluids” and “surface-to-surface radiation” were required to simulate illuminating LEDs adequately.

PRINCIPLES OF COMPILING A GERMAN-UKRAINIAN DICTIONARY OF PARONYMS

This article addresses the principles of selecting paronyms and the methodology for compiling an electronic German-Ukrainian dictionary of paronyms using a corpus-based approach and systematic analysis to identify similarities and differences in the use of paronyms in speech. The author presents a concept of paronymy as a systemic phenomenon involving etymologically related words with similar morphemic structures but different meanings. By conducting a comparative analysis of collocations, the study identified 1,836 paronyms organized into paronymic series, each comprising two to nine components. The article examines existing dictionaries of paronyms and highlights their lexicographic shortcomings, such as excessive normative/prescriptive orientation, inadequate development of dictionary entries from both linguistic and didactic perspectives, and a lack of rigorous evaluations of modern data to inform dictionary compilation. The ideal paronym dictionary should rely on corpus data, providing reliable information with generalizations about individual word uses within conventionalized language usage. Corpus-based tools, such as those used for contrasting near-synonyms, systematically identify similarities and differences between paronyms in a contrastive manner. This process determines the degree of semantic closeness among expressions with similar contextual usage by comparing their immediate collocational patterns. The recorded semantic closeness or distance between paronyms is based on their contextual overlap in usage. The lexicographic processing of the selected paronyms was carried out with TshwaneLex, a computer-based dictionary creation software that allows lexicographers to develop dictionaries for any language without requiring advanced IT skills. TshwaneLex offers various features such as automatic cross-reference tracking, advanced dictionary comparison/merge functionality, and support for all world languages through full Unicode compatibility. The lemma editing process uses a tree-based interface to represent the hierarchical structure of the lemma, including different meanings, submeanings, word formations, multi-word units, examples of usage, cross-references, and more. Furthermore, the input/output architecture is designed to support the development of additional interfaces for various data sources as add-ons or plug-ins, facilitating other output formats. The article notes that a PHP-based software module is currently available for hosting the TshwaneLex dictionary on the internet, providing an accessible platform for electronic dictionary publication.

Bus Location Tracking System

Bus Location Tracking System

The influence of activated carbon fiber paper structure on adsorption performance of cyclohexane

Activated carbon fibers paper (ACFP), made through wet-laid technology, had exhibited promising adsorption performance compared with granular and powdered activated carbon. This study prepared activated carbon fibers papers with different fibrous structures and investigated the dynamic adsorption performance of thin-layered ACFP against cyclohexane gas. The effects of inter-fiber pore size, dilution degree of activated carbon fibers, and porosity of the paper sheet on the adsorption performance were explored. The Bed Depth Service Time (BDST) model was employed for fitting and calculation, and the Flowdict module in Geodict software was used to analyze the flow field within the paper sheet. The results indicated that the inter-fiber pore size variation of ACFP had no significant effect on its adsorption breakthrough curve against cyclohexane gas. However, as the dilution degree of activated carbon fibers in the ACFP increased, the breakthrough time prolonged, and the adsorption utilization efficiency of activated carbon fibers continuously improved. Furthermore, decrease of ACFP porosity significantly impaired the adsorption performance. When the porosity decreased from 95.4 % to 91.4 %, the breakthrough adsorption capacity decreased from 134 mg/g to 95 mg/g, and the critical bed thickness increased from 0.029 cm to 0.044 cm.

Разработка модуля для управления моделированием системы двух сжимаемых жидких фаз с одной дисперсной фазой на базе платформы OpenFOAM

The purpose of the presented research is to refine the initial release of the graphical shell for the OpenFOAM package by designing and connecting an additional module focused on numerical experiments using the twoPhaseEulerFoam solver in the field of modeling problems in continuum mechanics. This module, unlike existing analogue applications, has the status of an open source software product, does not require the purchase of maintenance services, and has a Russian-language interface. In the presented software, to simplify further support and modification, the source code of the external part of the application is separated from the code that provides the operating logic. The key original approaches proposed by the author also include a subsystem for serializing design parameters, which allows you to convert the parameters of a design case into json and csv objects and perform the reverse process. This allows the user to switch between different parameter sets for one design case. In addition, it is worth emphasizing the presence in the created software module of a mechanism for checking the completeness of the design case before starting the numerical experiment. Some features of the solver and the principles of its use in preparing calculation cases are considered. The purpose of the study was determined and a list of required tasks was compiled. The selected technology stack is described, as well as development aids. A process diagram is provided to demonstrate how the application works, along with a description of each step. The results of the study were tested using the example of one of the fundamental problems of continuum mechanics and are presented in the form of an updated version of the graphical shell, publicly available on the GitHub resource. Based on the results of the study, the effectiveness of the selected technology stack for achieving development goals was confirmed, and the completed tasks were noted. The practical significance of the results is formulated, expressed in the potential saving of working time for engineers and researchers, minimizing modeling errors and simplifying the process of preparing a design case.

APPLICATION OF AUTOMATED SOFTWARE FOR OPERATIONAL HYDRAULIC CALCULATIONS OF A FIELD TRUNK PIPELINE

The article discusses the issues of improving the accuracy and efficiency of initial data preparation, as well as carrying out technical calculations when planning the route of field trunk pipelines (FTP) by automating the solution of tasks for: choosing the pipeline route according to a topographic map, constructing the profile of the pipeline route, conducting hydraulic calculation of the pipeline, determining the locations of pumping stations on the route and their operating modes. The results of the research carried out on the development of a software module for hydraulic calculation of field trunk pipelines for special software of the automated control system of the MTO «Palas» are presented.

Effects of Pd Alloying and Coating on the Galvanic Corrosion between Cu Wire and Bond Pads for a Semiconductor Packaging

Semiconductor chips are packaged in a process that involves creating a path to allow for signals to be exchanged with the outside world and ultimately achieving a form to protect against various external environmental conditions such as heat and moisture. The wire bonding type of packaging is a method in which thin metal wires are bonded to pads to create an electrical connection between the chip and the lead frame. An Epoxy Molding Compound (EMC) can be applied to protect semiconductor chips from external environmental conditions such as heat, shock, and moisture. However, EMC contains halogen elements and sulfides and has hydrophilic properties, which can lead to a corrosive environment. The present study aims to evaluate the influence of chloride, which is a contaminant formed during the PCB manufacturing process. To this end, the galvanic corrosion of bonding wire materials Cu wire, Cu wire alloyed with 1% Pd, and Cu wire coated with Pd was investigated. The first ball bond was bonded to the Al pad and the second stitch bond was bonded to the Au pad of the manufacturing process, after which the galvanic corrosion behavior in the semiconductor packaging module specimen was analyzed. A model of galvanic corrosion behavior was also proposed.

Exploring the impact of annealing temperature on morphological, structural, vibrational and electron paramagnetic resonance properties of starch-mediated spinel CoAl2O4: Experimental and DFT study

In the present work, CoAl2O4 nanoparticles were successfully synthesized using the simple auto-combustion sol-gel method employing starch as an organic fuel source. The effect of the annealing temperature on the structural, vibrational, morphological, and magnetic properties is studied. The obtained spherical nanoparticles have grain sizes ranging from 23.54 nm to 46.50 nm. X-ray diffraction (XRD) patterns reveal the formation of a face centered cubic (fcc) spinel phase with the Fd-3m space group for all prepared samples. The calculated average crystallite sizes exhibit an increase from 24.65 nm to 56.27 nm, consistent with the observed grain sizes. Density Functional Theory (DFT) calculations are applied to reach the optimized cell parameters as well as to confirm the structural properties of the synthetized CoAl2O4 nanoparticles. Geometry optimization of the CoAl2O4 spinel oxide is performed using the CASTEP module of Materials Studio software. The optimized unit cell, lattice parameter and unit cell volume were obtained from this simulation. The combined experimental and density functional theory study of structural properties of CoAl2O4 revealed that an increase in the calcination temperature leads to an increase in the volume of the unit cell and hence to an increase in the particles size. Fourier-transform infrared spectroscopy (FTIR) further corroborated these findings by demonstrating subtle shifts in characteristic CoAl2O4 absorption peaks with varying annealing temperatures. These peak shifts suggest a potential redistribution of Al³⁺ and Co2⁺ ions between tetrahedral and octahedral sites within the spinel structure. Electron paramagnetic resonance (EPR) spectroscopy revealed a magnetic state transition as a function of both the annealing temperature and the resulting crystallite size. Occupancy fluctuations of Al³⁺ and Co2⁺ ions at specific sites have also impacted on the nanoparticles color since the hue of the material depends on the valence state and the cationic coordination environment in the CoAl2O4 crystal lattice. Correlations between structural, vibrational, magnetic and color properties are presented to understanding how synthesis parameters influence CoAl2O4 characteristics which is essential for tailoring materials for specific applications.