Engineering Proceedings

Open AccessProceeding Paper

Application of Adaptive Algorithms on Ultrasound Imaging

by

Maryam Idrees

,

Hafiza Faheela

and

Faizan Ahsan Wali

Eng. Proc. 2023, 32(1), 25; https://doi.org/10.3390/engproc2023032025 - 23 May 2023

Abstract

Ultrasound, also known as ultrasonography, plays a major role in the medical imaging field. Ultrasound images are inevitably prone to different kinds of noise and speckle during their acquisition. Adaptive filters show the best performance in removing noise and speckles from images. In [...] Read more.

Ultrasound, also known as ultrasonography, plays a major role in the medical imaging field. Ultrasound images are inevitably prone to different kinds of noise and speckle during their acquisition. Adaptive filters show the best performance in removing noise and speckles from images. In this paper, we compared the least mean square algorithm, the quaternion least mean square algorithm, and the normalized least mean square algorithm for ultrasound image processing. It was demonstrated that NLMS displayed the best performance of these algorithms. The results are provided in order to illustrate the performance of algorithms. Full article

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Open AccessProceeding Paper

Monitoring the Condition of a Patient with Parkinson’s Disease

by

Yulia Shichkina

,

Roza Fatkieva

and

Nikita Isaenko

Eng. Proc. 2023, 33(1), 10; https://doi.org/10.3390/engproc2023033010 - 23 May 2023

Abstract

Currently, interest in the development of Internet-of-Things technologies is increasingly penetrating the field of clinical medicine. This paper provides an overview of the use of Internet-of-Things technologies in medical practice using the Scopus database of publications. The classification of publications on the topic [...] Read more.

Currently, interest in the development of Internet-of-Things technologies is increasingly penetrating the field of clinical medicine. This paper provides an overview of the use of Internet-of-Things technologies in medical practice using the Scopus database of publications. The classification of publications on the topic of research directions with promising development trends has been performed. With this in mind, the concept of the architecture of a system for monitoring the condition of a patient with Parkinson’s disease is presented. The necessary hardware and software solutions have been developed, taking into account the needs in order to more effectively adjust treatment and monitor the course of the disease. To more accurately determine the state of progression of the patient’s disease, tests have been designed and developed to assess overall emotional and physical well-being. For the most effective correction and control of drug therapy, a prototype of a drug administration device with four compartments for a drug has been designed, each compartment of which is individually controlled by a specially developed Bluetooth data transmission protocol. Access to each compartment is individual, which ensures the versatility of the device for taking several medications throughout the day. The practical application of the solution has also shown the relevance of its use in the task of studying the course of Parkinson’s disease as well as for monitoring the condition of a patient with existing concomitant diseases and the degree of their influence on the course of the underlying disease. Full article

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Open AccessProceeding Paper

Enhancing Phase Measurement by a Factor of Two in the Stokes Correlation

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Eng. Proc. 2023, 34(1), 4; https://doi.org/10.3390/HMAM2-14273 - 23 May 2023

Abstract

Phase loss is a typical problem in the optical domain, and optical detectors only measure the amplitude distribution of a signal without its phase. However, an optimal phase is desired in a variety of practical applications, such as optical metrology, nondestructive testing, and [...] Read more.

Phase loss is a typical problem in the optical domain, and optical detectors only measure the amplitude distribution of a signal without its phase. However, an optimal phase is desired in a variety of practical applications, such as optical metrology, nondestructive testing, and quantitative microscopy. Several methods have been proposed to quantitatively measure phase, among which interferometry is one of the most commonly used. An intensity interferometer has also been used to recover phase and enhance the phase difference measurement via the intensity correlation. In this paper, we present and examine another technique based on the Stokes correlation for enhancing phase measurement by a factor of two. The enhancement in phase measurement is accomplished through an evaluation of the correlation between two points of Stokes fluctuations of randomly scattered light and by recovering the enhanced phase of the object by using three-step phase shifting along with the Stokes correlations. This technique is expected to be useful for imaging and the experimental measurement of the phase of a weak signal. Full article

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Open AccessProceeding Paper

Adaptive Gaussian and Double Thresholding for Contour Detection and Character Recognition of Two-Dimensional Area Using Computer Vision

by

Nehal Abdul Rehman

and

Farah Haroon

Eng. Proc. 2023, 32(1), 23; https://doi.org/10.3390/engproc2023032023 - 22 May 2023

Abstract

Contour detection with good accuracy is challenging in various computer-aided measurement applications. This paper evaluates the performance and comparison of thresholding and edge detection techniques for contour measurement along with character detection and recognition between images of high and low quality. Thresholding is [...] Read more.

Contour detection with good accuracy is challenging in various computer-aided measurement applications. This paper evaluates the performance and comparison of thresholding and edge detection techniques for contour measurement along with character detection and recognition between images of high and low quality. Thresholding is one of the key techniques for pre-processing in computer vision. Adaptive Gaussian Thresholding (AGT) is applied to distinguish the foreground and background of an image, and Canny edge detection (CED) is used for spotting a wide range of edges. Adaptive Gaussian Thresholding works on a small set of neighboring pixels, while Canny Edge Detection takes high- and low-intensity pixels in the form of thresholds that are tested to find accurate contour measurements while retaining the maximum data contained within them. The results show that Adaptive Gaussian Thresholding outperforms Canny edge detection for both brightened sharp and blurry dull images. Full article

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Open AccessProceeding Paper

The System Architecture and Methods for Efficient Resource-Saving Scheduling in the Fog

by

Anna Klimenko

Eng. Proc. 2023, 33(1), 9; https://doi.org/10.3390/engproc2023033009 - 17 May 2023

Abstract

The problem of resource-saving scheduling in a fog environment is considered in this paper. The objective function of the problem in question presupposes the fog nodes’ reliability function maximizing. Therefore, to create a schedule, the following is required: the history of the fog [...] Read more.

The problem of resource-saving scheduling in a fog environment is considered in this paper. The objective function of the problem in question presupposes the fog nodes’ reliability function maximizing. Therefore, to create a schedule, the following is required: the history of the fog devices’ state changes and the search space, which consists of preselected nodes of the cloud-fog broker neighbourhood. The obvious approach to providing the scheduler with this information is to poll the fog nodes, yet this can consume the unacceptable time because of the QoS requirements. In this paper, the system architecture and general methods for efficient resource-saving scheduling is presented. The system is based on distributed ledger element usage, which provides the nodes with the proper awareness about the surroundings. The usage of the distributed ledger allows not only for the creation of the resource-saving schedule but also the reduction of the scheduling problem-solving time, which frees addition time that can be used for the solving of user tasks. The latter also affects the overall resource-saving via reliability. The novelty of this paper consists in the development of the hybrid ledger-based system, which integrates and arranges the elements of various ledger types to solve the newly formulated problem. Full article

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Open AccessProceeding Paper

Autonomous Navigation of Mobile Robot Assisted by Its Identified Neural Network Model ^†

by

Igor Prokopiev

,

Elizaveta Shmalko

and

Askhat Diveev

Eng. Proc. 2023, 33(1), 8; https://doi.org/10.3390/engproc2023033008 - 17 May 2023

Abstract

Autonomous navigation is one of the key tasks in the development of control systems for real autonomous mobile objects. This paper presents the developed technology for accurately determining the position of a mobile robot in an autonomous operating mode without an external positioning [...] Read more.

Autonomous navigation is one of the key tasks in the development of control systems for real autonomous mobile objects. This paper presents the developed technology for accurately determining the position of a mobile robot in an autonomous operating mode without an external positioning system. The approach involves using a high-precision model of a real robot identified by a neural network. The robot adjusts its position, determined using odometry and video camera, according to the position of the robot, obtained using an accurate model. To train the neural network, a training set is used that takes into account the features of the movement of a wheeled robot, including wheel slip. In the experimental part, the problem of autonomous movement of a mobile robot along a given trajectory is considered. Full article

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Open AccessProceeding Paper

Additional Requirement in the Formulation of the Optimal Control Problem for Applied Technical Systems

by

Elizaveta Shmalko

and

Askhat Diveev

Eng. Proc. 2023, 33(1), 7; https://doi.org/10.3390/engproc2023033007 - 16 May 2023

Abstract

This paper considers the difficulties that arise in the implementation of solutions to the optimal control problem. When implemented in real systems, as a rule, the object is subject to some perturbations, and the control obtained as a function of time as a [...] Read more.

This paper considers the difficulties that arise in the implementation of solutions to the optimal control problem. When implemented in real systems, as a rule, the object is subject to some perturbations, and the control obtained as a function of time as a result of solving the optimal control problem does not take into account these factors, which leads to a significant change in the trajectory and deviation of the object from the terminal goal. This paper proposes to supplement the formulation of the optimal control problem. Additional requirements are introduced for the optimal trajectory. The fulfillment of these requirements ensures that the trajectory remains close to the optimal one under perturbations and reaches the vicinity of the terminal state. To solve the problem, it is proposed to use numerical methods of machine learning based on symbolic regression. A computational experiment is presented in which the solutions of the optimal control problem in the classical formulation and with the introduced additional requirement are compared. Full article

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Open AccessProceeding Paper

Synthesis of a Feedback Controller by the Network Operator Method for a Mobile Robot Rosbot in Gazebo Environment

by

Elizaveta Shmalko

and

Yuri Rumyantsev

Eng. Proc. 2023, 33(1), 6; https://doi.org/10.3390/engproc2023033006 - 16 May 2023

Abstract

The article presents an approach based on machine learning with symbolic regression for the synthesis of a stabilization system for a mobile robot. This approach is universal and allows you to numerically solve the synthesis problem in a general setting without the need [...] Read more.

The article presents an approach based on machine learning with symbolic regression for the synthesis of a stabilization system for a mobile robot. This approach is universal and allows you to numerically solve the synthesis problem in a general setting without the need to form a training sample, instead relying only on the value of the functional. The synthesis is implemented to stabilize the mobile robot Rosbot in the Gazebo simulation environment. The feedback stabilization system is received by the network operator method. The advantage of the method is that it can be applied to a control object of any complexity and linearity. Full article

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Open AccessProceeding Paper

Extra-Super-Fast Charger for Electric Vehicles (EVs) and Plug-In Hybrid Electric Vehicles (PHEVs)

by

Mian Muhammad Amir Ayaz

,

Ajmal Farooq

and

Ihteshamul Haq

Eng. Proc. 2023, 32(1), 24; https://doi.org/10.3390/engproc2023032024 - 11 May 2023

Abstract

The main aim of this study is the development of a fast and secure charging system for electric vehicles. Recently, many different charging methods have been introduced. The main charging methods are the induction charging method and the conduction charging method. In this [...] Read more.

The main aim of this study is the development of a fast and secure charging system for electric vehicles. Recently, many different charging methods have been introduced. The main charging methods are the induction charging method and the conduction charging method. In this paper, the conduction charging method is employed. With regard to the conduction method, there are three levels of charging. At level 1, there is single-phase charging, while both single-phase and three-phase charging occur at level 2. Lastly, at level 3, a three-phase AC charging method, DC conduction charging method, and AC/DC conduction charging method is focused. The level 3 charging method is the main focus of this paper. Toward this end, a 12-diode rectifier or 12-pulse rectifier with a firing angle of zero degrees having two bridges is used for AC to DC conversion, while a SEPIC converter is used for DC-to-DC conversion. The design presented in this paper was simulated and verified using MATLAB/Simulink, and the results show that the Total Harmonic Distortion (THD) of the input current was reduced, and that overall efficiency was improved. Full article

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Open AccessProceeding Paper

Mobile Cloud Computing: A Survey on Current Security Trends and Future Directions

by

Bisma Sheikh

,

Ayesha Butt

and

Javeria Hanif

Eng. Proc. 2023, 32(1), 22; https://doi.org/10.3390/engproc2023032022 - 11 May 2023

Abstract

Mobile cloud computing (MCC) is an emerging concept that is gaining popularity in the IT sector. It is a significant topic of debate because it is being discussed as one of the most important trends for the future. After the COVID-19 pandemic, we [...] Read more.

Mobile cloud computing (MCC) is an emerging concept that is gaining popularity in the IT sector. It is a significant topic of debate because it is being discussed as one of the most important trends for the future. After the COVID-19 pandemic, we saw the rapid emergence of mobile computing, which also created massive hype over mobile application usage. This survey paper’s introduction is a literature review of the latest advanced prominent publications, highlighting its definition, infrastructure, advantages/limitations, and challenges, and is followed up with a discussion and results section, concluding with discussions on the future of MCC work that will be undertaken in the coming years. Full article

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Open AccessProceeding Paper

Using the STEGO Neural Network for Scintigraphic Image Analysis

by

Ivan Ulitin

,

Marina Barulina

and

Marina Velikanova

Eng. Proc. 2023, 33(1), 5; https://doi.org/10.3390/engproc2023033005 - 09 May 2023

Abstract

Currently, neural networks are being widely implemented for the diagnosis of various diseases, including cancer of various localizations and stages. The vast majority of such solutions use supervised or unsupervised convolutional neural networks, which require a great deal of training data. Using unsupervised [...] Read more.

Currently, neural networks are being widely implemented for the diagnosis of various diseases, including cancer of various localizations and stages. The vast majority of such solutions use supervised or unsupervised convolutional neural networks, which require a great deal of training data. Using unsupervised image segmentation algorithms can be considered the preferred trend since their use significantly reduces the complexity of neural network training. So, developing unsupervised image segmentation algorithms is one of the topical tasks of machine learning. This year, a team of developers from Google, MIT, and Cornell University developed the STEGO algorithm, which is an unsupervised and non-convolutional neural network. As its author stated, the STEGO algorithm performs well at image segmentation problems compared with other machine learning models. And this algorithm does not need a large amount of training data, unlike convolutional neural networks, which are widely used for medical image analysis. So, the aim of this work is to check the possibility of using this neural network for scintigraphy image segmentation by testing whether the STEGO algorithm is relevant when applied to a scintigraphy dataset. To achieve this goal, the intersection over union metric (IoU) was chosen for evaluating the correctness of the detection of the location of metastases. The training dataset consists of scintigraphic images of patients with various types of cancer and various metastasis appearances. Another version of this metric (mIoU, mean intersection over union) was also used by the creators of STEGO to assess the quality of the model to segment images with different kinds of content. Since the calculated metrics are not good enough, the use of this algorithm for scintigraphic image analysis is not possible or requires the development of a special methodology for this. Full article

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Open AccessProceeding Paper

Predictive Diagnosis of Breast Cancer Based on Cytokine Profile

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Eng. Proc. 2023, 33(1), 4; https://doi.org/10.3390/engproc2023033004 - 09 May 2023

Abstract

A predictive model for the early diagnosis of breast cancer based on the concentration of some cytokines in the tumor microenvironment in the blood was built in this paper. In the work, the influence of the following cytokines was studied: monocytic chemoattractant protein-1, [...] Read more.

A predictive model for the early diagnosis of breast cancer based on the concentration of some cytokines in the tumor microenvironment in the blood was built in this paper. In the work, the influence of the following cytokines was studied: monocytic chemoattractant protein-1, vascular endothelial growth factor, tumor necrosis factor-alpha, interferon gamma, transforming growth factor-beta1, granulocyte colony stimulating factor, and granulocyte-macrophage colony stimulating factor. As a result of preliminary statistical analysis, some combinations of these cytokines that allowed for almost reliable detection of the presence or absence of breast cancer were identified. Based on the identified combinations, new features were constructed. A machine learning model was trained using gradient boosting for its classification method. The built model has an accuracy equal to 1.0 at this stage, so the authors find it reasonable to carry out additional tests of the model for more patients. However, even at this stage, it can be concluded that the concentration of cytokines in the blood serum is applicable for the early diagnosis of breast cancer. Full article

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Open AccessProceeding Paper

Quality of Labeled Data in Machine Learning: Common Sense and the Controversial Effect for User Behavior Models

by

Maxim Bakaev

and

Vladimir Khvorostov

Eng. Proc. 2023, 33(1), 3; https://doi.org/10.3390/engproc2023033003 - 09 May 2023

Abstract

Intelligent systems today are increasingly required to predict or imitate human perception and behavior. In this, feature-based Machine Learning (ML) models are still common, since collecting appropriate training data from human subjects for the data-hungry Deep Learning models is costly. Considerable effort is [...] Read more.

Intelligent systems today are increasingly required to predict or imitate human perception and behavior. In this, feature-based Machine Learning (ML) models are still common, since collecting appropriate training data from human subjects for the data-hungry Deep Learning models is costly. Considerable effort is put into ensuring data quality, particularly in crowd-annotation platforms (e.g., Amazon MTurk), where fees of top workers can be several times higher than the median. The common knowledge is that quality of input data is beneficial for the end quality of ML models, though quantitative estimations of the effect are rare. In our study, we investigate how labeled data quality affects the accuracy of models that predict users’ subjective impressions—per the scales of Complexity, Aesthetics and Orderliness assessed by 70 subjects. The material, about 500 web page screenshots, was also labeled by 11 workers of varying diligence, whose work quality was validated by another 20 verifiers. Unexpectedly, we found significant negative correlations between the workers’ precision and

R^{2}

s of the models, for two out of the three scales (

r_{11} = - 0.768

for Aesthetics,

r_{11} = - 0.644

for Orderliness). We speculate that the controversial effect might be explained by a bias in the indiligent labelers’ output that corresponds to subjectivity in human perception of visual objects. Full article

Open AccessProceeding Paper

Optimality Conditions for the Principle of Trajectory Division

by

Valentin Bereznev

Eng. Proc. 2023, 33(1), 2; https://doi.org/10.3390/engproc2023033002 - 09 May 2023

Abstract

This paper considers the problem of controlling a mobile robot in the presence of circular obstacles. To solve this problem, it is proposed to use the previously suggested principle of dividing permissible trajectories into a sequence of rectilinear sections and arcs of circles [...] Read more.

This paper considers the problem of controlling a mobile robot in the presence of circular obstacles. To solve this problem, it is proposed to use the previously suggested principle of dividing permissible trajectories into a sequence of rectilinear sections and arcs of circles that are the boundaries of circular obstacles. The conditions for the solution based on this principle of optimality are obtained. Full article

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Open AccessProceeding Paper

Novel Electrochemical Lactate Biosensors Based on Prussian Blue Nanoparticles

by

Vladislav Pleshakov

,

Elena Daboss

and

Arkady Karyakin

Eng. Proc. 2023, 35(1), 2; https://doi.org/10.3390/IECB2023-14572 - 08 May 2023

Abstract

We report on the novel electrochemical lactate biosensors based on Prussian blue nanoparticles. The immobilization of lactate oxidase was performed through drop-casting on the sensor surface of a mixture containing enzyme, (3-aminopropyl)triethoxysilane and isopropyl alcohol. The apparent Michaelis constant and inactivation constant were [...] Read more.

We report on the novel electrochemical lactate biosensors based on Prussian blue nanoparticles. The immobilization of lactate oxidase was performed through drop-casting on the sensor surface of a mixture containing enzyme, (3-aminopropyl)triethoxysilane and isopropyl alcohol. The apparent Michaelis constant and inactivation constant were determined (0.29 ± 0.03 mM and 0.042 ± 0.002 min⁻¹, respectively) and compared with values obtained for biosensors based on Prussian blue films. The developed lactate biosensors are not inferior in characteristics to those previously known, while the manufacturing process is less laborious. Obtained values also indicate that lactate biosensors based on Prussian blue nanoparticles and lactate oxidase have sufficient sensitivity and operational stability for analytical application in medical and biological research. Full article

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Open AccessEditorial

Statement of Peer Review

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Eng. Proc. 2023, 33(1), 1; https://doi.org/10.3390/engproc2023033001 - 08 May 2023

Abstract

In submitting conference proceedings to Engineering Proceedings, the volume editors of the proceedings certify to the publisher that all papers published in this volume have been subjected to peer review that was administered by the volume editors [...] Full article

Open AccessProceeding Paper

Self-Assembled Monolayers for Uricase Enzyme Absorption Immobilization on Screen-Printed Gold Electrodes Modified

by

Héctor David Hernández

,

Rocio B. Dominguez

and

Juan Manuel Gutiérrez

Eng. Proc. 2023, 35(1), 1; https://doi.org/10.3390/IECB2023-14575 - 08 May 2023

Abstract

Miniaturized and integrated devices for fast determination of clinical biomarkers are in high demand in the current healthcare environment. In this work, we present a functionalized self-assembled monolayer (SAM) on the gold surface of a screen-printed electrode (Au-SPE). The device was applied for [...] Read more.

Miniaturized and integrated devices for fast determination of clinical biomarkers are in high demand in the current healthcare environment. In this work, we present a functionalized self-assembled monolayer (SAM) on the gold surface of a screen-printed electrode (Au-SPE). The device was applied for uric acid (UA) detection, a biomarker associated with arthritis, diabetes mellitus, and kidney function. Prior to SAM formation, AuSPE was subjected to pretreatment with KOH and Au electrodeposition to provide additional roughness to the substrate. The SAM was formed in the AuSPE/KOH/AuNP surface by the cysteamine method—carried out for working surface dipping in the cysteamine (CYS) solution at 20 mM for 24 h (rinsed with ethanol and milli-Q water). Then, the uricase enzyme was immobilized through physical absorption at room temperature for 1 h to obtain the AuSPE/KOH/AuNPs/SAM/Uox biosensor. The physical and electrochemical characterization of AuSPE modification was carried out by scanning electron microscopy (SEM) and cyclic voltammetry (CV). The calibrated data of the Au/KOH/AuNPs/SAM/Uox biosensor showed a linear relation in the range of 50–1000 µM, a sensibility of 0.1449 µA/[(µM)cm²], and a limit of detection (LOD) of 4.4669 µM. The Au/KOH/AuNPs/SAM/Uox also exhibited good selectivity for UA in the presence of ascorbic acid. Moreover, the methodology showed good reproducibility, stability, and sensitive detection of UA. This performance of the proposed biosensor is in good accordance with clinical needs and can be compared with previous biosensors based on nanostructured surfaces of high-fabrication complexity. Full article

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Open AccessProceeding Paper

Semantic Segmentation for Various Applications: Research Contribution and Comprehensive Review

by

Madiha Mazhar

,

Saba Fakhar

and

Yawar Rehman

Eng. Proc. 2023, 32(1), 21; https://doi.org/10.3390/engproc2023032021 - 05 May 2023

Abstract

Semantic image segmentation is used to analyse visual content and carry out real-time decision-making. This narrative literature analysis evaluates the multiple innovations and advancements in the semantic algorithm-based architecture by presenting an overview of the algorithms used in medical image analysis, lane detection, [...] Read more.

Semantic image segmentation is used to analyse visual content and carry out real-time decision-making. This narrative literature analysis evaluates the multiple innovations and advancements in the semantic algorithm-based architecture by presenting an overview of the algorithms used in medical image analysis, lane detection, and face recognition. Numerous groundbreaking works are examined from a variety of angles (e.g., network structures, algorithms, and the problems addressed). A review of the recent development in semantic segmentation networks, such as U-Net, ResNet, SegNet, LCSegnet, FLSNet, and GNet, is presented with evaluation metrics across a range of applications to facilitate new research in this field. Full article

Open AccessProceeding Paper

Simultaneous Upstream and Inter Optical Network Unit Communication for Next Generation PON

by

Saba Ahmed

,

Rizwan Aslam Butt

and

Muhammad Imran Aslam

Eng. Proc. 2023, 32(1), 20; https://doi.org/10.3390/engproc2023032020 - 05 May 2023

Abstract

In traditional passive optical network (PON) neighboring, optical network units (ONUs) cannot communicate directly but through optical line terminals, resulting in propagation delays, security hazards and unnecessary use of upstream and downstream bandwidth. Inter optical network unit communication (IOC) can be a promising [...] Read more.

In traditional passive optical network (PON) neighboring, optical network units (ONUs) cannot communicate directly but through optical line terminals, resulting in propagation delays, security hazards and unnecessary use of upstream and downstream bandwidth. Inter optical network unit communication (IOC) can be a promising solution for these problems. IOC is mostly demonstrated with the help of dedicated or tunable transceivers increasing the cost of the system and making it complex. Transceiver sharing is also demonstrated in the literature but this will be a bandwidth-inefficient technique. In our paper, the simultaneous transmission of IOC signal and upstream signal is demonstrated in a time-division-multiplexed PON using single transmitter and self-phase modulation-based wavelength convertor at each ONU that converts the upstream wavelength of 1310 nm to 1310.6 nm when IOC signal is being transmitted by that ONU; at the same time another ONU can transmit the upstream data at 1310 nm which results in efficient bandwidth utilization with less delays compared to the traditional PON. In our proposed design the IOC signal is reflected back by a Uniform Fiber Bragg Grating and the upstream signal is transmitted through it. This design supports a data rate of 25 Giga bits/sec. Full article

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