Software Part Research Articles

Future Scope and Current Energy Situation of Wind Energy, with a Simulation of Small Wind Farm in Matrix Laboratory (MATLAB)

When the world is going through extreme energy shortage, mainly the non-renewable energies, wind energy is the hope along with solar energy, hydro energy, nuclear energy and bio mass energy to meet the energy demand. In the end of 2021, in India only, the wind capacity was 40 GWatt [8]. By the end of 2030, new 30 GWatt offshore wind capacity will be installed [8]. Wind turbines may be of various shapes and sizes. When more than one wind turbines are working together to create electrical power, they form a wind farm. The aim of this particular project is to make a simulation of a small wind farm of 4.5 MW in the simulation part of MATLAB software. Here squirrel cage induction generators are used as the electrical generators connected to the turbines. It generates power for the grid. SVC is connected to the wind turbines to control the overall reactive power. The aim is to make a MATLAB Simulink phasor model of a 4.5 MW wind farm with SVC with three fully functioning wind turbines.

Data Interactive Control System Based on Heterogeneous Database of Information Fusion and Internet of Things

Abstract To improve the data interaction control effect of a heterogeneous database and reduce packet loss rate and response time, a new heterogeneous database data interaction control system based on information fusion is designed. The system consists of hardware and software parts. The hardware part of the heterogeneous database data interaction control system is composed of a data extraction module, data sending and receiving module, encryption module, and data interaction control module. On the basis of completing hardware design, the system software is designed, a fuzzy similarity matrix is constructed by calculating the similarity among the evidence, the weight coefficient of each piece of evidence is calculated by calculating the support function of each piece of evidence, the evidence source model is modified by using discount rules, and Dempster–Shafer combination rules are transformed into matrix analysis. Combined with the modified evidence source model, information fusion of the heterogeneous database is carried out to complete the software design of the data interactive control system. The experimental results show that the data interaction control effect of the heterogeneous database in this system is good, and the packet loss rate and response time are low, improving the data interaction control effect.

Control system for noise-resistant electronic speed controller of a brushless electric motor for an unmanned aerial vehicle

Objectives. The high demand for unmanned aircraft and their efficiency makes the production of their components a matter of relevance. One of these components is the speed controller of the brushless electric motor of the propeller motor group. At the current time, Russian industry, however, does not mass-produce them. In order to start production, control methods and algorithms for the hardware and software parts of devices of this type are needed. Criteria for selecting the main components also need to be formalized. The aim of this work is to develop a method for the software control of electric motors. This includes block diagrams and invariant algorithms and methods for the calculated selection of parameters of the main microcontroller of the electronic speed controller.Methods. Methods of algorithmization, expert assessments, linear computational processes and experimental studies were used.Results. The paper presents the theoretical basis for controlling the required motors. It proposes a block diagram of the implementation of the controller, and a technique for switching windings when controlling with a trapezoidal signal is proposed. Examples are given in the form of an oscillogram. Based on theoretical research, an invariant algorithmic apparatus was developed for building software for various types of microcontrollers. Block diagrams of all the main modules of the software are also presented. The main ones include: the event switching algorithm; and the main endless loop of the microcontroller. The requirements for microcontrollers to create the various types of speed controllers are formalized herein and presented in the form of a set of mathematical expressions. They enable the number of required peripheral devices and microcontroller ports to be calculated according to the requirements for the microcontroller, as well as the computing power of the core used.Conclusions. Experimental studies show the reliability of the theoretical research presented herein. The results obtained can be used to select the optimal element base and develop software for speed controllers of electric motors of the propellers of unmanned aircraft.

SMART TRAFFIC LIGHTS USING IOTTECHNOLOGIES : PROJECT CONCEPT AND PROGRESS

The rural exodus and population growth has led to the rapid expansion of cities without sometimes developing road infrastructure. This situation is at the origin of congestion in road traffic with a very high number of vehicles. In Africa, cities that have the financial means often use traffic lights with a predefined traffic plan which can be ineffective at sometimes of the day. In this paper, we propose a concept of wireless traffic light terminal, connected and self-sufficient in energy, for installation at intersections without public works on the road. This traffic light terminal is accessible remotely from police stations for its supervision and control. Thus, traffic management at an intersection is carried out remotely and in real time by an agent who selects a traffic plan adapted to the current situation. The objective is to centralize, with few personnel, the management of several intersections equipped with traffic light terminals, for better overall regulation of road traffic at low costs. Our work resulted in a proof of concept, for a four-lane crossroads, made with four Arduino electronic boards, four Lora wireless modules, a Raspberry-pi microcomputer, a camera and a 4G modem. For the software part, a server application developed with the node-red language, on the Raspberry-pi electronic card, provides the graphical interface for monitoring and control. The proposed system integrates a Cloud service that makes the human-machine interface for supervision and control remotely accessible via the Internet.

BICYCLE PARKING STAND

This paper presents the design and construction of a bicycle parking stand that protects a standing bicycle from theft. The design includes the construction principles, a 3D model made in SolidEdge software, the electronic components used in the construction of the stand and an electronic schematic with control software. The stand consists of mechanical (stand, handle), electronic (microcontroller, display, RFID system) and software (C++ language) parts. The stand was made and tested under real conditions, which confirmed the effectiveness of the system. The bicycle stand can be used in all public areas where bicycle parking should be safe.

IMPROVING THE SYSTEM OF MOBILE DEVICES FOR DETERMINING THE COORDINATES OF SOUND ANOMALIES

The simulation of the operation of devices for determining the coordinates of sound anomalies, which is located on board mobile devices of monitoring systems, is considered. The calculation based on the data of the coordinates of sound anomalies, which were measured in the connected coordinate system of a separate device, coordinates in a single basic system, is substantiated. The model of the error calculation process was built and modeled taking into account the influence of the angular velocity of the carrier device for a separate device. It is proposed based on the results of modeling the hardware and software parts of the device.
 This study is devoted to the modeling of devices embedded in mobile monitoring systems designed to detect sound anomalies. These devices play a crucial role in identifying and tracking the coordinates of such anomalies. The research focuses on elucidating the computational methods used to transform the coordinates of sound anomalies, originally measured in a linked coordinate system of individual devices, into coordinates within a single reference system.
 An important aspect of this study is the construction of a model to estimate the error accumulation process. This model takes into account the influence of the angular velocity of the carrier on individual components. By simulating various scenarios, the study aims to accurately quantify and understand the sources of errors inherent in the system.
 In addition, the study offers recommendations for improving the hardware and software components of the device based on the information obtained during the simulation process. These recommendations include hardware additions and strategic reallocation of software components to mitigate errors and improve the overall efficiency and accuracy of audio anomaly detection systems.

Aggregation of Risk Management and Non-Parametric Models to Rank Failure Modes of Radio Frequency Identification Systems

The failure mode causes and effects analysis (FMCEA) is a commonly used reliability approach. It identifies, predicts, and analyzes potential failure modes affecting the proper function of equipment or the process under study, along with their roots and consequences. FMCEA aims to evaluate and assess the risks resulting from their occurrence, intending to suggest corresponding repair, adjustment, and precautionary measures to be planned during the conception, instruction, or implementation stages. However, the FMCEA has been criticized in the literature for its many inherent shortcomings related to risk assessment and prioritization. Therefore, this study presents an enhanced FMCEA method to address the deficiencies of the traditional risk priority number (RPN) and improve the reliability of risk assessments and corrective actions. A data envelopment analysis (DEA), as a non-parametric method, is used to evaluate the efficiency of these failures by considering their fixing time and cost and deciding on their final priority ranks. Sub-failure modes and their interrelationships are also taken into account. The radio frequency identification (RFID) system was chosen as an example due to its core role in Industry 4.0 and the Internet of Things (IoT) to demonstrate the effectiveness and usefulness of the proposed method. A total of 67 failures related to both hardware and software parts, including the environmental impacts of this technology, have been disclosed. The results of the conventional and the suggested FMCEA methods are found to be considerably different, with ten failure modes classified as being the most efficient.

Real-time Tracking System for Distribution Information of Logistics Enterprises Based on IOT Technology

Logistics enterprise distribution information real-time tracking system in the actual application process, there is the problem of low cargo throughput, this study was aimed to design a kind of logistics enterprise distribution information real-time tracking system based on Internet of Things technology. In hardware part: control the reading and writing equipment according to the predetermined working mode, adjust the parameters of the reader, connect the circuit and other accessories; in software part: increase the correlation between the tables by setting foreign keys, build the logistics enterprise distribution information database, control and supervise the logistics activities. The result shows that the average value of cargo throughput between the real-time tracking system of distribution information of logistics enterprises in the paper and two other real-time tracking systems of logistics enterprises is 1412.14 T/H, 1049.38 T/H and 1088.81 T/H respectively, indicating that the real-time tracking system of distribution information of logistics enterprises designed after the application of IOT technology is more perfect.

Event and data persistency models for the LHCb Real Time Analysis System

Starting in 2022, the upgraded LHCb detector is collecting data with a pure software trigger. In its first stage, reducing the rate from 30MHz to about 1MHz, GPUs are used to reconstruct and trigger on B and D meson topologies and high-pT objects in the event. In its second stage, a CPU farm is used to reconstruct the full event and perform candidate selections, which are persisted for offline use with an output rate of about 10GB/s. Fast data processing, flexible and custom-designed data structures tailored for SIMD architectures and efficient storage of the intermediate data at various steps of the processing pipeline onto persistent media, e.g. tapes is essential to guarantee the full physics program of LHCb. We present the event model and data persistency developments for the trigger of LHCb in Run 3. Particular emphasis is given to the novel software-design aspects with respect to the Run 1+2 data taking, the performance improvements which can be achieved and the experience of restructuring a major part of the reconstruction software in a large HEP experiment.

Software Testing Using Cuckoo Search Algorithm with Machine Learning Techniques

Software testing are any errors, flaws, bugs, mistakes, failures in a piece of software that might cause the programme to produce incorrect or unexpected results. Testing in software almost always increase both the time and money needed to finish a project. And finding bugs and fixing them is a laborious and expensive software process in and of itself. While it's unrealistic to expect to completely eradicate all testing from a project, their severity may be mitigated. It is possible to predict where bugs may appear in software using a method known as software defect prediction (SDP). The goal of each software development project should be to provide a bug-free product. Predicting where bugs may appear in code, often known as software defect prediction (SDP), is an important part of fixing software. Software of a high calibre should have few bugs. A software metric is a quantitative or qualitative evaluation of some aspect of the programme or its requirements. One of the more recent population-based algorithms, Cuckoo Search (CS) was inspired by the flight patterns of some cuckoo species as well as the Lévy flying patterns of other birds and fruit flies. The needs for international convergence are met by CS. KNN is a significant non-parameter supervised learning technique. This paper presents an overview of Stochastic Diffusion Search (SDS) in the form of a social metaphor to illustrate the processes by which SDS allots resources. The best-fit pattern identification and matching difficulties were addressed by SDS using a novel probabilistic method. As a multiagent population-based global search and optimization method, SDS is a distributed model of computing that makes use of interaction amongst basic agents. The behaviour of SDS is described by studying its resource allocation, convergence to global optimum, resilience, minimum convergence criterion, and linear time complexity within a rigorous mathematical framework, setting it apart from many nature-inspired search algorithms. This paper proposes a hybrid optimization strategy based on CS-SDS techniques. By using the global search strategy solution of the SDS algorithm, this hybridization idea aims to enhance the cuckoo bird's search strategy for the optimum host nest. To that end, the SDS method would be used to place the cuckoo egg in the most advantageous location. When compared to other classifiers, PC2's improved performance may be attributed to its higher recall values. When compared to the Naive Bayes and Radial Bias Neural Network classifiers, the KNN performs 7.64% and 2.20% better, respectively.

APLAN: open assembly planning framework in FreeCAD

In the latest decade, the consumer’s desire for personalisation has clearly taken of, challenging manufacturers to diversify their product portfolio while maintaining the same (or near) mass-produced prices. As a result, production is nowadays geared towards low volumes with high variety for which adaptive assembly systems are required. Hence, being able to automatically map out the assembly of complex products yields significant strategic advantages over competing manufacturers. Although a wide range of assembly sequencing algorithms have been developed in the past, researchers and companies still experience intellectual and financial thresholds to applying these software packages themselves. Either the algorithms have to be largely re-engineered from scientific literature, or are offered as part of costly commercial CAD software in the form of plugins and add-ons. However, in some cases, the developed source code is made publicly available via online collaboration platforms though in a variety of programming languages and often requiring the cumbersome installation of additional software libraries.Out of these needs, the proposed APLAN module arose: a software framework allowing developers to share their (dis)assembly planning algorithms in a centralised, uniform manner through the open-source 3D parametric modelling software FreeCAD. As impetus, several in-house developed algorithms for determining topological and geometrical (dis)assembly constraints are included as well as an academic (dis)assembly planner. Previously, such algorithms had to be executed via the terminal, after which the extensive liaison, blocking, and AND/OR graphs were outputted as text or static images. Through APLAN, users are now able to inspect and edit these graphs interactively and dynamically. To conclude, this manuscript finally reports on the benchmarking of the aforementioned connection and obstruction detectors, and their academic and industrial application for human-robot collaboration.

Design and Realization of Calorify Mobile Application Interface with Augmented Reality Technology

A mobile smartphone is an integral part of the modern world, and not only for communication, but also for the possibility of using it for many other functions, from entertainment to security measures. An important components of mobile smartphone software are mobile applications, the demand for which is growing every year. One of the directions is mobile applications for maintenance, management, monitoring and support of a healthy lifestyle. This work is devoted to the development and implementation of the "fronend" part of the user interface software of the Calorify mobile application of a hybrid type intended for calorie counting. Despite the large number of mobile applications for counting calories, there is a need to develop a mobile application of a hybrid type with more ergonomic design solutions, confirmed by calculating calories based on analytical mathematical dependencies, with the implementation of augmented reality technology by scanning products. To realize the set goal, prototyping was first carried out in the Figma templating environment and the design of the future Calorify user interface was created. Next, modern UI toolkit technology was used in conjunction with the UI builder in the Unity engine to implement Calorify interfaces. UI Builder allows you to visually create and edit user interface resources, such as user interface documents (.uxml) and style sheets (.uss), used with the UI Toolkit. In general, the Calorify application consists of registration, user, main page and bottom menu pages. The scanner is located in the lower menu block, it is the main function of the Calorify application, which is the main difference and novelty of the developed mobile application. This button opens the option of taking a photo of the dish to automatically determine its calorie and nutritional value. This is a quick and convenient way to get product information the process of scanning products in Calorify, which implements augmented reality technology. For further development, it is planned to expand the possibility of registering domains of electronic addresses, to expand the database and filling of pages.

Classification of MRI brain tumors based on registration preprocessing and deep belief networks

<abstract><p>In recent years, augmented reality has emerged as an emerging technology with huge potential in image-guided surgery, and in particular, its application in brain tumor surgery seems promising. Augmented reality can be divided into two parts: hardware and software. Further, artificial intelligence, and deep learning in particular, have attracted great interest from researchers in the medical field, especially for the diagnosis of brain tumors. In this paper, we focus on the software part of an augmented reality scenario. The main objective of this study was to develop a classification technique based on a deep belief network (DBN) and a softmax classifier to (1) distinguish a benign brain tumor from a malignant one by exploiting the spatial heterogeneity of cancer tumors and homologous anatomical structures, and (2) extract the brain tumor features. In this work, we developed three steps to explain our classification method. In the first step, a global affine transformation is preprocessed for registration to obtain the same or similar results for different locations (voxels, ROI). In the next step, an unsupervised DBN with unlabeled features is used for the learning process. The discriminative subsets of features obtained in the first two steps serve as input to the classifier and are used in the third step for evaluation by a hybrid system combining the DBN and a softmax classifier. For the evaluation, we used data from Harvard Medical School to train the DBN with softmax regression. The model performed well in the classification phase, achieving an improved accuracy of 97.2%.</p></abstract>

Design of Face Detection and Recognition System to Enhance Security of Safe Locker

In recent years, safe lockers have been spread in public places to secure valuable belongings. The people are concerned about losing safe locker keys or use of the spare key by others and will remain worried about their things. To solve the forenamed matter, this paper proposed a system that depends on biometrics to secure valuable things and can minimize their concerns and worries. The proposed system consists of two major parts, software, and hardware. In the hardware part, A microcontroller with a camera and an electronic lock will be used to securely open or close the door of the safe locker. In the software part, the images that are pictured by the camera will be prepared by an image processing algorithm and then Support Vector Machines (SVM) will be trained in the images of a person. The images and information of the person will be saved until the belongings come out and after that deletes everything to prepare for another one. Index Terms— Safe Locker, Face Detection, Face Recognition, Machine Learning, Cyber Security.

Feedforward Neural Network-Based Indoor Air Quality Detection System

Indoor air quality is crucial for the sustainability of human life quality. Therefore, improving indoor air quality is critical for enhancing life quality. In this study, an artificial intelligence-based indoor air quality monitoring system is designed. The system consists of two main parts, hardware and software. The hardware part includes a control card and various sensors. The software part includes a C-based IDE software and a feedforward network, a deep learning algorithm, for establishing the connection between the control card and the sensors. The temperature, humidity, and gas concentration values obtained from the sensors at certain intervals were fed to the feedforward network's input layer through the control card. The feedforward network consists of the input layer, hidden layer, and output layer, and the decision on whether the air quality is normal or not was made at the output. The system described in this study is intended to provide a real-time monitoring solution for indoor air quality. By using a feedforward neural network, the system is able to learn patterns in the sensor data and detect changes in air quality that may indicate a problem. The system can be customized to suit the needs of different environments and can be used in a variety of settings, including homes, offices, and public spaces. Ultimately, the goal of the system is to improve human health and well-being by ensuring that indoor air quality is at a safe and healthy level.

РАСЧЕТ ЭЛЕМЕНТОВ ЖЕЛЕЗОБЕТОННЫХ КОНСТРУКЦИЙ НА ОГНЕСТОЙКОСТЬ И ОГНЕСОХРАННОСТЬ В ПРОГРАММНОМ КОМПЛЕКСЕ СТАРКОН.

RCDiagra software as a part of the domestic STARKON software is presented. The software is designed to perform fire resistance and fire safety analysis of reinforced concrete beams and columns. The strength analysis is based on the nonlinear deformation theory and enables to take into account non-stationary thermal effects changing the concrete and reinforcement properties. To determine the ultimate strength, elastic modulus for concrete and reinforcement, ultimate relative deformations, a thermal analysis is performed in accordance with SP 468.1325800.2019 and MDS 21-2.2000. The thermal engineering analysis solve the problem of determining the temperature field in the beam cross-section under non-stationary thermal action, depending on the boundary conditions and thermophysical parameters of the material. It is assumed that the coefficients of thermal conductivity and specific heat capacity of concrete depend on the current temperature at the crosssection points.

Application of Electronic Communication Signal Modulation Recognition System Based on Fourier Transform

Abstract In this paper, the weighted class fractional Fourier transform is redefined by means of the weighted superposition of state functions, and the Fourier transform is applied to dissect the intrinsic relationship between the M-WFRFT and the 4-WFRFT and to obtain the weighting coefficients of the electronic communication signals. On the basis of the WFRFT discrete algorithm, the electronic communication signal is expanded to include M a term after the M -WFRFT and the hybrid carrier modulation method based on the WFRFT is given. According to the design idea of the electronic communication system, the hardware part and software part of the electronic communication system are designed, and the electronic communication signal modulation recognition system is experimentally analyzed by using the simulation experiment method. The results show that when the signal-to-noise ratio is -8dB and the optimization algorithms are the Sgd algorithm, Sgdm algorithm, and Adam algorithm, the modulation identification accuracy of OFDM signal is 39.3%, 57.5% and 43.5%, respectively, which indicates that the Sgdm optimization algorithm is the most suitable one compared with other algorithms, and it is more effective in the modulation identification of OFDM signals at low signal-to-noise ratio. The number of scans of the three-layer multi-parameter WFRFT signal by the non-cooperative party is 6.4 × 1013 times, and the increase in the number of scans leads to an increase in the cost paid by the non-cooperative party, which confirms that the secure communication system based on three-layer weighted fractional-order Fourier transform has good resistance to parameter scanning characteristics and high confidentiality. This study further improves the a priori parameter setting of the electronic communication system and enhances its complexity, resulting in better anti-interception identification features.

The Design of a Location Monitoring System for a Fleet of Electric Scooters

The development of geolocation systems( geostationary satellite networks), as well as devices capable of receiving signals and processing the data coming from them, makes possible the implementation of location monitoring systems for various purposes. Whether it's about security or optimizing travel times or routes, these systems are based on information in the form of global coordinates (latitude and longitude) from satellite systems or cell towers. The design of such a system is presented in this paper, being a good guide in the design and implementation of such a system, regardless of the application. Both, the hardware part (the designed equipment) and the software part (the backend component running on a virtual private server, as well as a mobile application) are presented in this paper. In the development of the system, was used only location provided by information from satellites, without using GSM cell signals. The entire system has been successfully tested in different GSM signal conditions as well as various locations to see the influence of environmental parameters on performance. The system described in the paper can be the starting point for the development of other systems for a variety of applications that require the management of the location of some devices.

HPC-driven computational reproducibility in numerical relativity codes: a use case study with IllinoisGRMHD

Reproducibility of results is a cornerstone of the scientific method. Scientific computing encounters two challenges when aiming for this goal. Firstly, reproducibility should not depend on details of the runtime environment, such as the compiler version or computing environment, so results are verifiable by third-parties. Secondly, different versions of software code executed in the same runtime environment should produce consistent numerical results for physical quantities. In this manuscript, we test the feasibility of reproducing scientific results obtained using the IllinoisGRMHD code that is part of an open-source community software for simulation in relativistic astrophysics, the Einstein Toolkit. We verify that numerical results of simulating a single isolated neutron star with IllinoisGRMHD can be reproduced, and compare them to results reported by the code authors in 2015. We use two different supercomputers: Expanse at SDSC, and Stampede2 at TACC. By compiling the source code archived along with the paper on both Expanse and Stampede2, we find that IllinoisGRMHD reproduces results published in its announcement paper up to errors comparable to round-off level changes in initial data parameters. We also verify that a current version of IllinoisGRMHD reproduces these results once we account for bug fixes which have occurred since the original publication.

An improved method and means with the function of automatic adjustment of electrical signal parameters for detection of the recurrent laryngeal nerve

The article presents the results of the development of software and hardware for identifying the recurrent laryngeal nerve (RLN). In the course of research, it was found that the effectiveness of detecting as result of stimulation of the RLN with a pulsed electric current depends on its frequency. On this basis, it is proposed to use software tools for automatically adjusting electrical signal parameters in order to stimulate the tissues of a surgical wound as efficiently as possible. In thyroid surgery, these tools are used to minimize the risk of damage to the RLN. An improved method for stimulating surgical wound tissue is presented. The main algorithms of the tools and the architecture of the software part are presented. The proposed device was tested on the basis of a medical centre in Ukraine.