Special Issue "Perspectives and Challenges in Doctoral Research—Selected Papers from the 10th Edition of the Scientific Conference of the Doctoral Schools of “Dunărea de Jos” University of Galati (SCDS-UDJG)"

A special issue of Inventions (ISSN 2411-5134).

Deadline for manuscript submissions: 31 December 2022 | Viewed by 3965

Special Issue Editors

Prof. Dr. Gabriela Rapeanu
E-Mail Website
Guest Editor
Faculty of Food Science and Engineering, "Dunarea de Jos" University of Galati, Galați, Romania
Interests: biologically active compound extraction and characterization; degradation and inactivation kinetics of biological active compounds; encapsulation techniques; food authentication

Special Issue Information

Dear Colleagues,

We are inviting submissions to a Special Issue of the Invention journal for participation in the 10th edition of the Scientific Conference of the Doctoral Schools from “Dunărea de Jos” University of Galaţi. The objective of the 2022 Conference is to bring together perspectives and challenges in doctoral research to a common forum. The aim of the conference is to provide a platform to the doctoral researchers to meet and share state of the art developments in their field. On this occasion, our institution targets to promote excellence in research, to set up partnerships and collaborative relationships through the exchange of knowledge and expertise. As in the previous editions, the conference invites oral and poster presentations in sections related to the main domains of the doctoral research at UDJG. Workshops, exhibition stands, and social activities are also included in the programme, all with the aim of developing and improving the network of the doctoral schools.

All the papers presented in the conference and accepted for publication in this Special Issue will benefit of a 50% discount for the APC.

Prof. Dr. Eugen Rusu
Prof. Dr. Gabriela Rapeanu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Inventions is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • advanced research in mechanical and industrial engineering
  • progress in food science and bio-resources engineering
  • advances in engineering and management in agriculture and rural development
  • advanced research in electrical/electronic engineering, system engineering and information technologies
  • future of eco-nanotechnologies, functional materials and coatings
  • chemistry
  • electrochemistry in life sciences

Published Papers (7 papers)

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Research

Article
Event-Based PID Control of a Flexible Manufacturing Process
Inventions 2022, 7(4), 86; https://doi.org/10.3390/inventions7040086 - 26 Sep 2022
Viewed by 98
Abstract
In most cases, the system control is made in a sampled manner, measuring the controlled value at a predefined frequency given by the sampling time. However, not all processes provide relevant information at regular intervals, especially in manufacturing. To reduce the costs and [...] Read more.
In most cases, the system control is made in a sampled manner, measuring the controlled value at a predefined frequency given by the sampling time. However, not all processes provide relevant information at regular intervals, especially in manufacturing. To reduce the costs and complexity of systems, event-based measuring is necessary. To control this kind of process, an event-based controller is needed. This poses some challenges, especially between the event-triggered measurement, as the process runs in an open loop. In the literature, most event-based controllers are based on the comparison of the error value with a predefined value and activate the controller if this value is crossed. However, in this type of controller, the measured value is measured at a predefine interval and is not suited for most event-based processes. In manufacturing systems, the most usual event-based process is represented by the conveyor transportation system. In this process, the product position is measured only in key locations on the conveyor. For the optimal operation of a flexible manufacturing system, the presence of a product in a key location at predetermined intervals is necessary. For this purpose, this article presents an event-based PID controller implemented on a conveyor transportation system. Full article
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Article
Sensitivity Analysis of Artificial Neural Networks Identifying JWH Synthetic Cannabinoids Built with Alternative Training Strategies and Methods
Inventions 2022, 7(3), 82; https://doi.org/10.3390/inventions7030082 - 13 Sep 2022
Viewed by 267
Abstract
This paper presents the alternative training strategies we tested for an Artificial Neural Network (ANN) designed to detect JWH synthetic cannabinoids. In order to increase the model performance in terms of output sensitivity, we used the Neural Designer data science and machine learning [...] Read more.
This paper presents the alternative training strategies we tested for an Artificial Neural Network (ANN) designed to detect JWH synthetic cannabinoids. In order to increase the model performance in terms of output sensitivity, we used the Neural Designer data science and machine learning platform combined with the programming language Python. We performed a comparative analysis of several optimization algorithms, error parameters and regularization methods. Finally, we performed a new goodness-of-fit analysis between the testing samples in the data set and the corresponding ANN outputs in order to investigate their sensitivity. The effectiveness of the new methods combined with the optimization algorithms is discussed. Full article
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Article
Wind Variation near the Black Sea Coastal Areas Reflected by the ERA5 Dataset
Inventions 2022, 7(3), 57; https://doi.org/10.3390/inventions7030057 - 07 Jul 2022
Viewed by 461
Abstract
In the context of the European Green Deal implementation, it is expected that there will be an increase in number of the wind farms located near the coastal areas in order to support this initiative. The Black Sea represents an important source of [...] Read more.
In the context of the European Green Deal implementation, it is expected that there will be an increase in number of the wind farms located near the coastal areas in order to support this initiative. The Black Sea represents an important source of wind energy, and as a consequence, in the present work the regional wind resources (onshore and offshore) are evaluated by considering a total of 20 years of ERA5 wind data covering the 20-year time interval from January 2002 to December 2021. From a general perspective, it is clear that the offshore areas (100 km from the shoreline) are defined by much higher wind speed values than in the onshore, reaching an average of 8.75 m/s for the points located on the western sector. During the winter, these values can go up to 8.75 m/s, with the mention that the northern sectors from Ukraine and Russia may easily exceed 8 m/s. In terms of the wind turbines’ selection, for the offshore areas defined by consistent wind resources, generators will be considered that are defined by a rated wind speed of 11 m/s. Finally, we can mention that a theoretical offshore wind turbine of 20 MW can reach a capacity factor located between 20.9 and 48.3%, while a maximum annual electricity production of 84.6 GWh may be obtained from the sites located near the Romanian and Ukrainian sectors, respectively. Full article
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Article
Mobile Visual Servoing Based Control of a Complex Autonomous System Assisting a Manufacturing Technology on a Mechatronics Line
Inventions 2022, 7(3), 47; https://doi.org/10.3390/inventions7030047 - 22 Jun 2022
Viewed by 492
Abstract
The main contribution of this paper is the modeling and control for a complex autonomous system (CAS). It is equipped with a visual sensor to operate precision positioning in a technology executed on a laboratory mechatronics line. The technology allows the retrieval of [...] Read more.
The main contribution of this paper is the modeling and control for a complex autonomous system (CAS). It is equipped with a visual sensor to operate precision positioning in a technology executed on a laboratory mechatronics line. The technology allows the retrieval of workpieces which do not completely pass the quality test. Another objective of this paper is the implementation of an assisting technology for a laboratory processing/reprocessing mechatronics line (P/RML) containing four workstations, assisted by the following components: a complex autonomous system that consists of an autonomous robotic system (ARS), a wheeled mobile robot (WMR) PeopleBot, a robotic manipulator (RM) Cyton 1500 with seven degrees of freedom (7 DOF), and a mobile visual servoing system (MVS) with a Logitech camera as visual sensor used in the process of picking, transporting and placing the workpieces. The purpose of the MVS is to increase the precision of the RM by utilizing the look and move principle, since the initial and final positions of the CAS can slightly deviate from their trajectory, thus increasing the possibility of errors to appear during the process of catching and releasing the pieces. If the processed piece did not pass the quality test and has been rendered as defective, it is retrieved from the last station of the P/RML and transported to the first station for reprocessing. The control of the WMR is done using the trajectory-tracking sliding-mode control (TTSMC). The RM control is based on inverse kinematics model, and the MVS control is implemented with the image moments method. Full article
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Article
Communication and Control of an Assembly, Disassembly and Repair Flexible Manufacturing Technology on a Mechatronics Line Assisted by an Autonomous Robotic System
Inventions 2022, 7(2), 43; https://doi.org/10.3390/inventions7020043 - 15 Jun 2022
Viewed by 667
Abstract
This paper aims to describe modeling and control in what concerns advanced manufacturing technology running on a flexible assembly, disassembly and repair on a mechatronic line (A/D/RML) assisted by an Autonomous Robotic System (ARS), two robotic manipulators (RM) and visual servoing system (VSS). [...] Read more.
This paper aims to describe modeling and control in what concerns advanced manufacturing technology running on a flexible assembly, disassembly and repair on a mechatronic line (A/D/RML) assisted by an Autonomous Robotic System (ARS), two robotic manipulators (RM) and visual servoing system (VSS). The A/D/RML consists of a six workstations (WS) mechatronics line (ML) connected to a flexible cell (FC) equipped with a 6-DOF ABB industrial robotic manipulator (IRM) and an ARS used for manipulation and transport. A hybrid communication and control based on programmable logic controller (PLC) architecture is used, which consists of two interconnected systems that feature both distributed and centralized topology, with specific tasks for all the manufacturing stages. Profinet communication link is used to interconnect and control FC and A/D/RML. The paper also discusses how to synchronize data between different field equipment used in the industry and the control systems. Synchronization signals between the master PLC and ARS is performed by means of Modbus TCP protocol and OPC UA. The structure of the ARS consists of a wheeled mobile robot (WMR) with two driving wheels and one free wheel (2DW/1FW) equipped with a 7-DOF RM. Trajectory tracking sliding-mode control (TTSMC) is used to control WMR. The end effector of the ARS RM is equipped with a mobile eye-in-hand VSS technology for the precise positioning of RM to pick and place the workparts in the desired location. Technology operates synchronously with signals from sensors and from the VSS HD camera. If the workpiece does not pass the quality test, the process handles it by transporting back from the end storage unit to the flexible cell where it will be considered for reprocessing, repair or disassembling with the recovery of the dismantled parts. The recovered or replaced components are taken over by the ARS from disassembling location and transported back to the dedicated storage warehouses to be reused in the further assembly processes. Full article
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Article
Image Moment-Based Features for Mass Detection in Breast US Images via Machine Learning and Neural Network Classification Models
Inventions 2022, 7(2), 42; https://doi.org/10.3390/inventions7020042 - 15 Jun 2022
Viewed by 585
Abstract
Differentiating between malignant and benign masses using machine learning in the recognition of breast ultrasound (BUS) images is a technique with good accuracy and precision, which helps doctors make a correct diagnosis. The method proposed in this paper integrates Hu’s moments in the [...] Read more.
Differentiating between malignant and benign masses using machine learning in the recognition of breast ultrasound (BUS) images is a technique with good accuracy and precision, which helps doctors make a correct diagnosis. The method proposed in this paper integrates Hu’s moments in the analysis of the breast tumor. The extracted features feed a k-nearest neighbor (k-NN) classifier and a radial basis function neural network (RBFNN) to classify breast tumors into benign and malignant. The raw images and the tumor masks provided as ground-truth images belong to the public digital BUS images database. Certain metrics such as accuracy, sensitivity, precision, and F1-score were used to evaluate the segmentation results and to select Hu’s moments showing the best capacity to discriminate between malignant and benign breast tissues in BUS images. Regarding the selection of Hu’s moments, the k-NN classifier reached 85% accuracy for moment M1 and 80% for moment M5 whilst RBFNN reached an accuracy of 76% for M1. The proposed method might be used to assist the clinical diagnosis of breast cancer identification by providing a good combination between segmentation and Hu’s moments. Full article
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Article
A Fingerprint Matching Algorithm Using the Combination of Edge Features and Convolution Neural Networks
Inventions 2022, 7(2), 39; https://doi.org/10.3390/inventions7020039 - 27 May 2022
Cited by 2 | Viewed by 711
Abstract
This study presents an algorithm for fingerprint classification using a CNN (convolutional neural network) model and making use of full images belonging to four digital databases. The main challenge that we face in fingerprint classification is dealing with the low quality of fingerprints, [...] Read more.
This study presents an algorithm for fingerprint classification using a CNN (convolutional neural network) model and making use of full images belonging to four digital databases. The main challenge that we face in fingerprint classification is dealing with the low quality of fingerprints, which can impede the identification process. To overcome these restrictions, the proposed model consists of the following steps: a preprocessing stage which deals with edge enhancement operations, data resizing, data augmentation, and finally a post-processing stage devoted to classification tasks. Primarily, the fingerprint images are enhanced using Prewitt and Laplacian of Gaussian filters. This investigation used the fingerprint verification competition with four databases (FVC2004, DB1, DB2, DB3, and DB4) which contain 240 real fingerprint images and 80 synthetic fingerprint images. The real images were collected using various sensors. The innovation of the model is in the manner in which the number of epochs is selected, which improves the performance of the classification. The number of epochs is defined as a hyper-parameter which can influence the performance of the deep learning model. The number of epochs was set to 10, 20, 30, and 50 in order to keep the training time at an acceptable value of 1.8 s/epoch, on average. Our results indicate the overfitting of the model starting with the seventh epoch. The accuracy varies from 67.6% to 98.7% for the validation set, and between 70.2% and 75.6% for the test set. The proposed method achieved a very good performance compared to the traditional hand-crafted features despite the fact that it used raw data and it does not perform any handcrafted feature extraction operations. Full article
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