Special Issue "Design Automation, Computer Engineering, Computer Networks and Social Media (SEEDA-CECNSM 2021)"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: closed (15 March 2022) | Viewed by 14492

Special Issue Editors

Prof. Dr. Markos G. Tsipouras
E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, University of Western Macedonia, GR50100 Kozani, Greece
Interests: biomedical signal processing; EEG signal processing; data mining; decision support and medical expert systems; data modelling; computational intelligence; image processing; biomedical engineering
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Alexandros T. Tzallas
E-Mail Website
Guest Editor
School of Informatics and Telecommunications, Department of Informatics and Telecommunications, University of Ioannina, Kostakioi, GR-47100 Arta, Greece
Interests: biomedical signal processing; EEG signal processing; brain computer interface systems; wearable devices; image processing; decision support and medical expert systems; biomedical engineering
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Nikolaos Giannakeas
E-Mail Website
Guest Editor
School of Informatics and Telecommunications, Department of Informatics and Telecommunications, University of Ioannina, Kostakioi, GR-47100 Arta, Greece
Interests: biomedical image and signal processing; EEG signal processing; brain computer interface systems; wearable devices; bioinformatics; machine learning; biomedical engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Katerina D. Tzimourta
E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, University of Western Macedonia, GR50100 Kozani, Greece
Interests: biomedical signal processing; EEG signal processing; brain–computer interface; machine learning; EEG wearable devices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 6th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM 2021) will take place in Preveza, Greece, from 24 to 26 September 2021. The SEEDA-CECNSM technical program includes all aspects of Information Science and Technology. This Special Issue aims at publishing extended versions of papers in the area of Information Technology from the conference. Potential topics include (but are not limited to) the following:

  • Artificial intelligence and applications;
  • CAD tools and algorithms;
  • Numerical and scientific computation;
  • Embedded systems and applications;
  • Social networks and information technologies in education;
  • Digital media technologies;
  • Information technologies in e-Commerce, e-Services, and e-Government;
  • Industrial informatics;
  • Open-source tools;
  • Smart and sociable ecosystems.

Prof. Dr. Markos G. Tsipouras
Prof. Dr. Alexandros T. Tzallas
Prof. Dr. Nikolaos Giannakeas
Dr. Katerina D. Tzimourta
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. Information is an international peer-reviewed open access monthly 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 1400 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

  • Artificial intelligence
  • CAD tools
  • Numerical and scientific computation
  • Embedded systems
  • Information technologies in education
  • Social networks
  • Digital media technologies
  • e-Commerce
  • e-Services
  • e-Government
  • Industrial informatics
  • Open-source tools
  • Smart and sociable ecosystems

Published Papers (16 papers)

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Research

Article
Design of a Fuzzy Logic Controller for the Double Pendulum Inverted on a Cart
Information 2022, 13(8), 379; https://doi.org/10.3390/info13080379 - 08 Aug 2022
Viewed by 404
Abstract
The double-inverted pendulum (DIP) constitutes a classical problem in mechanics, whereas the control methods for stabilizing around the equilibrium positions represent the classic standards of control system theory and various control methods in robotics. For instance, it functions as a typical model for [...] Read more.
The double-inverted pendulum (DIP) constitutes a classical problem in mechanics, whereas the control methods for stabilizing around the equilibrium positions represent the classic standards of control system theory and various control methods in robotics. For instance, it functions as a typical model for the calculation and stability of walking robots. The present study depicts the controlling of a double-inverted pendulum (DIP) on a cart using a fuzzy logic controller (FLC). A linear-quadratic controller (LQR) was used as a benchmark to assess the effectiveness of our method, and the results showed that the proposed FLC can perform significantly better than the LQR under a variety of initial system conditions. This performance is considered very important when the reduction of the peak system output is concerned. The proposed controller equilibration and velocity tracking performance were explored through simulation, and the results obtained point to the validity of the control method. Full article
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Article
A Routing and Task-Allocation Algorithm for Robotic Groups in Warehouse Environments
Information 2022, 13(6), 288; https://doi.org/10.3390/info13060288 - 06 Jun 2022
Viewed by 687
Abstract
In recent years, the need for robotic fleets in large warehouse environments has constantly increased. The customers require faster services concerning the delivery of their products, making the use of systems such as robots and order-management software more than essential. Numerous researchers have [...] Read more.
In recent years, the need for robotic fleets in large warehouse environments has constantly increased. The customers require faster services concerning the delivery of their products, making the use of systems such as robots and order-management software more than essential. Numerous researchers have studied the problem of robot routing in a warehouse environment, aiming to suggest an efficient model concerning the robotic fleet’s management. In this research work, a methodology is proposed, providing feasible solutions for optimal pathfinding. A novel algorithm is proposed, which combines Dijkstra’s and Kuhn–Munkers algorithms efficiently. The proposed system considers the factor of energy consumption and chooses the optimal route. Moreover, the algorithm decides when a robot must head to a charging station. Finally, a software tool to visualize the movements of the robotic fleet and the real-time updates of the warehouse environment was developed. Full article
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Article
Efficient Edge-AI Application Deployment for FPGAs
Information 2022, 13(6), 279; https://doi.org/10.3390/info13060279 - 28 May 2022
Viewed by 899
Abstract
Field Programmable Gate Array (FPGA) accelerators have been widely adopted for artificial intelligence (AI) applications on edge devices (Edge-AI) utilizing Deep Neural Networks (DNN) architectures. FPGAs have gained their reputation due to the greater energy efficiency and high parallelism than microcontrollers (MCU) and [...] Read more.
Field Programmable Gate Array (FPGA) accelerators have been widely adopted for artificial intelligence (AI) applications on edge devices (Edge-AI) utilizing Deep Neural Networks (DNN) architectures. FPGAs have gained their reputation due to the greater energy efficiency and high parallelism than microcontrollers (MCU) and graphical processing units (GPU), while they are easier to develop and more reconfigurable than the Application Specific Integrated Circuit (ASIC). The development and building of AI applications on resource constraint devices such as FPGAs remains a challenge, however, due to the co-design approach, which requires a valuable expertise in low-level hardware design and in software development. This paper explores the efficacy and the dynamic deployment of hardware accelerated applications on the Kria KV260 development platform based on the Xilinx Kria K26 system-on-module (SoM), which includes a Zynq multiprocessor system-on-chip (MPSoC). The platform supports the Python-based PYNQ framework and maintains a high level of versatility with the support of custom bitstreams (overlays). The demonstration proved the reconfigurabibilty and the overall ease of implementation with low-footprint machine learning (ML) algorithms. Full article
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Article
Teaching Informatics to Adults of Vocational Schools during the Pandemic: Students’ Views and the Role of Neuroeducation
Information 2022, 13(6), 274; https://doi.org/10.3390/info13060274 - 26 May 2022
Viewed by 661
Abstract
The COVID-19 pandemic has had an extremely significant impact on the educational process. The need to continue the educational practice, albeit the restrictions imposed in movement, led to a change in the way students participate and learn, as well as in the way [...] Read more.
The COVID-19 pandemic has had an extremely significant impact on the educational process. The need to continue the educational practice, albeit the restrictions imposed in movement, led to a change in the way students participate and learn, as well as in the way educators teach and communicate. The aim of the present research study was to record the perspectives and views of adult students of evening upper secondary schools of the informatics sector, in relation to the challenges, experiences and learning involvement in the online courses. The study was conducted using a questionnaire with open-ended questions given to all students of an evening vocational upper secondary school in a semi-urban island region. The findings show that the way students are taught, the distractions and responsibilities of the students as well as their feelings concerning the pandemic, were the major challenges they faced. Those challenges affected both their involvement and learning experiences from the educational process. Finally, it seems that the low interaction among students and educators, the technical difficulties, and the lack of a structured learning framework have had an impact on the effectiveness of online education, according to educational neuroscience principles. Full article
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Article
Shortest Path Algorithms for Pedestrian Navigation Systems
Information 2022, 13(6), 269; https://doi.org/10.3390/info13060269 - 25 May 2022
Viewed by 671
Abstract
Efficient shortest path algorithms are of key importance for routing and navigation systems. However, these applications are designed focusing on the requirements of motor vehicles, and therefore, finding paths in pedestrian sections of urban areas is not sufficiently supported. In addition, finding the [...] Read more.
Efficient shortest path algorithms are of key importance for routing and navigation systems. However, these applications are designed focusing on the requirements of motor vehicles, and therefore, finding paths in pedestrian sections of urban areas is not sufficiently supported. In addition, finding the shortest path is often not adequate for urban sidewalk routes, as users of these applications may also be interested in alternative routes that, although slightly longer, possess other desirable features and properties. According to the literature, the search for alternative routes is carried out mainly using the k-shortest paths (KSP) algorithm which represents an ordered list of all available alternatives. Even though various KSP algorithms have been proposed, to the best of our knowledge, there is no research addressing all issues inherent in a pedestrian navigation system. The purpose of this paper is to present a heuristic algorithm for graph datasets that implements a penalty-based method which, by increasing certain edge weights, effectively searches for the most accessible alternative paths in multi-route cases. To demonstrate how the algorithm works, we present experimental results on finding the most accessible paths in pedestrian sections of the historical center of Thessaloniki city. Full article
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Article
Creative Narration as a Design Technique
Information 2022, 13(6), 266; https://doi.org/10.3390/info13060266 - 24 May 2022
Viewed by 578
Abstract
Creative narration is a structured ideation technique based on storytelling. It has the potential to enhance the initial design process of ideation in terms of collaboration and creativity. People from various disciplines, following specific steps, collaborate to create a story. Afterward, inspired by [...] Read more.
Creative narration is a structured ideation technique based on storytelling. It has the potential to enhance the initial design process of ideation in terms of collaboration and creativity. People from various disciplines, following specific steps, collaborate to create a story. Afterward, inspired by their stories, they create products and services. In this paper, two case studies are presented and compared, where the technique of creative narration was used in the contexts of two creative workshops. An initial assessment of this process, highlighting the strong and weak points of the technique, is discussed in this paper. Full article
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Article
Enhancing Core Public Service Vocabulary to Enable Public Service Personalization
Information 2022, 13(5), 225; https://doi.org/10.3390/info13050225 - 27 Apr 2022
Viewed by 1063
Abstract
The provision of public services (PS) is at the heart of public authority operations as it directly affects citizens’ lives and the prosperity of society. Part of PS provision is publishing PS descriptions in an online catalogue to inform citizens and promote transparency. [...] Read more.
The provision of public services (PS) is at the heart of public authority operations as it directly affects citizens’ lives and the prosperity of society. Part of PS provision is publishing PS descriptions in an online catalogue to inform citizens and promote transparency. The European Commission has developed Core Public Service Vocabulary Application Profile (CPSV-AP), as a standard European PS data model to facilitate PS catalogue creation and semantic interoperability. However, CPSV-AP is not sufficient to model complex PS with different versions based on rules and citizens’ circumstances (e.g., getting a passport for a child or for an emergency). As a result, citizens cannot obtain personalized information on PS. The aim of this paper is to enhance CPSV-AP in order to support the modeling of complex PS. We illustrate the use of the proposed model in a real-life case study. Specifically, we use the proposed model to develop a knowledge graph and a chatbot that provides personalized information to citizens of the city of Bjelovar (Croatia) regarding the life-event “having a baby”. We believe our research is of interest to researchers on PS data models and public authorities interested in providing personalized PS information to their citizens using chatbots. Full article
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Article
Enhancing Food Supply Chain Security through the Use of Blockchain and TinyML
Information 2022, 13(5), 213; https://doi.org/10.3390/info13050213 - 20 Apr 2022
Cited by 4 | Viewed by 1186
Abstract
Food safety is a fundamental right in modern societies. One of the most pressing problems nowadays is the provenance of food and food-related products that citizens consume, mainly due to several food scares and the globalization of food markets, which has resulted in [...] Read more.
Food safety is a fundamental right in modern societies. One of the most pressing problems nowadays is the provenance of food and food-related products that citizens consume, mainly due to several food scares and the globalization of food markets, which has resulted in food supply chains that extend beyond nations or even continent boundaries. Food supply networks are characterized by high complexity and a lack of openness. There is a critical requirement for applying novel techniques to verify and authenticate the origin, quality parameters, and transfer/storage details associated with food. This study portrays an end-to-end approach to enhance the security of the food supply chain and thus increase the trustfulness of the food industry. The system aims at increasing the transparency of food supply chain monitoring systems through securing all components that those consist of. A universal information monitoring scheme based on blockchain technology ensures the integrity of collected data, a self-sovereign identity approach for all supply chain actors ensures the minimization of single points of failure, and finally, a security mechanism, that is based on the use of TinyML’s nascent technology, is embedded in monitoring devices to mitigate a significant portion of malicious behavior from actors in the supply chain. Full article
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Article
Exploiting Net Connectivity in Legalization and Detailed Placement Scenarios
Information 2022, 13(5), 212; https://doi.org/10.3390/info13050212 - 20 Apr 2022
Viewed by 803
Abstract
Standard-cell placement is the fundamental step in a typical VLSI/ASIC design flow. Its result, paired with the outcome of the routing procedure can be the decisive factor in rendering a design manufacturable. Global placement generates an optimized instance of the design targeting a [...] Read more.
Standard-cell placement is the fundamental step in a typical VLSI/ASIC design flow. Its result, paired with the outcome of the routing procedure can be the decisive factor in rendering a design manufacturable. Global placement generates an optimized instance of the design targeting a set of metrics, while ignoring rules pertaining its feasibility. Legalization and detailed placement rectify this situation, attempting to attain minimum quality loss by often disregarding the connectivity between cells and making runtime the focal point of these steps. In this article, we present a set of variations on a connectivity-based legalization scheme that can either be applied as a legalizer or a detailed placer. The variations can be applied in the entirety of the chip area or in the confinement of a user-specified bin while they are guided by various optimization goals, e.g., total wire length, displacement and density. We analytically describe our variations and evaluate them through extensive simulations on commonly used benchmarks. Full article
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Article
A Traffic-Load-Based Algorithm for Wireless Sensor Networks’ Lifetime Extension
Information 2022, 13(4), 202; https://doi.org/10.3390/info13040202 - 15 Apr 2022
Viewed by 748
Abstract
It has been shown in the literature that the lifetime of a wireless sensor network is heavily connected to the number of transmissions that network nodes have to undertake. Considering this finding, along with the effects of the energy hole problem where nodes [...] Read more.
It has been shown in the literature that the lifetime of a wireless sensor network is heavily connected to the number of transmissions that network nodes have to undertake. Considering this finding, along with the effects of the energy hole problem where nodes closer to the sink node transmit more than the more distant ones, a node close to the sink node will be the one that transmits the most, while it will also be the node that will deplete its battery first. Taking into consideration that the failure of a single network node to operate, due to its battery being discharged, can lead to a network stopping its operation, the most energy-consuming node in the network will also be the one that will be responsible for the network’s termination. In this sense, the most energy-consuming node’s energy consumption optimization is the main case in this paper. More specifically, in this work, it is firstly shown that the energy consumption of a wireless sensor network is closely related to each network node’s traffic load, that is the transmissions of the packets that are created or forwarded by a node. The minimization of the most energy-consuming node’s energy consumption was studied here, while the implementation of a traffic-load-based algorithm is also proposed. Under the proposed algorithm, given a simple shortest path approach that assigns a parent (i.e., the next hop towards the sink node) in each network node and the knowledge it provides regarding the distance (in hops in this paper’s case) of network nodes from the sink node, the proposed algorithm exploits the shortest path’s results in order to discover, for all network nodes, neighbors that are of the same distance (from the sink node) with the initially assigned parent. Then, if such neighbors exist, all these neighbors are equally burdened with the parenting role. As a result, the traffic load is shared by all of them. To evaluate the proposed algorithm, simulation results are provided, showing that the goals set were achieved; thus, the network lifetime was prolonged. In addition, it is shown that under the algorithm, a fairer distribution of the traffic load takes place. Full article
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Article
Low Power EEG Data Encoding for Brain Neurostimulation Implants
Information 2022, 13(4), 194; https://doi.org/10.3390/info13040194 - 12 Apr 2022
Viewed by 648
Abstract
Neurostimulation devices applied for the treatment of epilepsy that collect, encode, temporarily store, and transfer electroencephalographic (EEG) signals recorded intracranially from epileptic patients, suffer from short battery life spans. The principal goal of this study is to implement strategies for low power consumption [...] Read more.
Neurostimulation devices applied for the treatment of epilepsy that collect, encode, temporarily store, and transfer electroencephalographic (EEG) signals recorded intracranially from epileptic patients, suffer from short battery life spans. The principal goal of this study is to implement strategies for low power consumption rates during the device’s smooth and uninterrupted operation as well as during data transmission. Our approach is organised in three basic levels. The first level regards the initial modelling and creation of the template for the following two stages. The second level regards the development of code for programming integrated circuits and simulation. The third and final stage regards the transmitter’s implementation at the evaluation level. In particular, more than one software and device are involved in this phase, in order to achieve realistic performance. Our research aims to evolve such technologies so that they can transmit wireless data with simultaneous energy efficiency. Full article
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Article
Multicriteria Approach for Design Optimization of Lightweight Piezoelectric Energy Harvesters Subjected to Stress Constraints
Information 2022, 13(4), 182; https://doi.org/10.3390/info13040182 - 02 Apr 2022
Viewed by 761
Abstract
In this work a multicriteria optimization approach to minimize weight and maximize power output in piezoelectric energy harvesting systems for aerospace applications is studied. The design variables are the geometric and electric circuit parameters of the vibration-based piezoelectric energy harvester (PEH). A finite [...] Read more.
In this work a multicriteria optimization approach to minimize weight and maximize power output in piezoelectric energy harvesting systems for aerospace applications is studied. The design variables are the geometric and electric circuit parameters of the vibration-based piezoelectric energy harvester (PEH). A finite element model is developed to model the dynamic behavior of the composite plate-type harvester with embedded piezoelectric layers. The cantilever PEH structure is subjected to constraints in the bending stresses which must be lower than or equal to the tensile yield strength of the piezoelectric material. For solving the multi-objective optimization problem, the Non-dominated Sorting Genetic Algorithm II (NSGA-II), the Non-dominated Sorting Genetic Algorithm III (NSGA-III) and the Generalized Differential Evolution 3 (GDE3) algorithm are employed. It is shown that the proposed algorithms are effective in developing optimal Pareto front curves for maximum electrical power output and minimum mass of the PEH system. A comparative assessment of the solutions generated on the Pareto Front show that GDE3 achieved solutions that generate higher maximum power output and performs better compared to the two other algorithms. Full article
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Article
A Game-Based Learning Approach in Digital Design Course to Enhance Students’ Competency
Information 2022, 13(4), 177; https://doi.org/10.3390/info13040177 - 31 Mar 2022
Cited by 1 | Viewed by 1109
Abstract
Digital Design is a laboratory course, and the educator must focus on the students’ need to know why they study the theory and mainly on the transition from knowledge-based learning to competency-based learning. This study consists of five surveys that were conducted during [...] Read more.
Digital Design is a laboratory course, and the educator must focus on the students’ need to know why they study the theory and mainly on the transition from knowledge-based learning to competency-based learning. This study consists of five surveys that were conducted during 2017–2021. First, we evaluated students’ learning outcomes in order to define possible learning problems. According to the literature, gamification can have a positive impact on students’ motivation and learning outcomes. Therefore, we used ready-made digital games in order to evaluate students’ satisfaction and willingness toward their integration in the educational process. This process was repeated in the next academic year. The feedback we received from the previous surveys has helped us to adapt to the new approaches of teaching due to the current pandemic caused by COVID-19. We proposed an online holistic environment based on Keller’s (1987) ARCS model and Malone’s (1981) motivational model, which was applied in distance learning. Each student participated in a student-centered learning experience. He took an active role and was self-manager of his learning process. He was given the opportunity to develop capabilities and strategies through practice and engagement in higher-order cognitive activities, acquire self-learning skills, learn how to solve problems, and participate in teamwork. This study’s innovation is that students experienced a combination of learning approaches: (a) a virtual lab consisting of simulation-based activities, which allowed students to access new laboratory experiences, (b) a project-based digital game without a processor, which developed their motivation, creativity, and hands-on ability, as opposed to the other relevant studies that use ready-made games, and (c) asynchronous videos as feedback, which ensured the educator’s emotional support and social presence. Finally, this study developed research to evaluate the effectiveness of this online holistic environment and used a questionnaire, which was created based on Keller’s Instructional Materials Motivation Survey tool. The results showed that its integration in distance learning is probable to motivate students to learn and affect positively their attention, relevance, confidence, and satisfaction. Full article
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Article
Ensemble Convolutional Neural Network Classification for Pancreatic Steatosis Assessment in Biopsy Images
Information 2022, 13(4), 160; https://doi.org/10.3390/info13040160 - 23 Mar 2022
Viewed by 787
Abstract
Non-alcoholic fatty pancreas disease (NAFPD) is a common and at the same time not extensively examined pathological condition that is significantly associated with obesity, metabolic syndrome, and insulin resistance. These factors can lead to the development of critical pathogens such as type-2 diabetes [...] Read more.
Non-alcoholic fatty pancreas disease (NAFPD) is a common and at the same time not extensively examined pathological condition that is significantly associated with obesity, metabolic syndrome, and insulin resistance. These factors can lead to the development of critical pathogens such as type-2 diabetes mellitus (T2DM), atherosclerosis, acute pancreatitis, and pancreatic cancer. Until recently, the diagnosis of NAFPD was based on noninvasive medical imaging methods and visual evaluations of microscopic histological samples. The present study focuses on the quantification of steatosis prevalence in pancreatic biopsy specimens with varying degrees of NAFPD. All quantification results are extracted using a methodology consisting of digital image processing and transfer learning in pretrained convolutional neural networks for the detection of histological fat structures. The proposed method is applied to 20 digitized histological samples, producing an 0.08% mean fat quantification error thanks to an ensemble CNN voting system and 83.3% mean Dice fat segmentation similarity compared to the semi-quantitative estimates of specialist physicians. Full article
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Article
Teacher Perceptions on Virtual Reality Escape Rooms for STEM Education
Information 2022, 13(3), 136; https://doi.org/10.3390/info13030136 - 05 Mar 2022
Cited by 1 | Viewed by 1747
Abstract
Science, technology, engineering, and mathematics (STEM) is a meta-discipline employing active, problem-centric approaches such as game-based learning. STEM competencies are an essential part of the educational response to the transformations caused by the fourth industrial revolution, spearheaded by the convergence of multiple exponential [...] Read more.
Science, technology, engineering, and mathematics (STEM) is a meta-discipline employing active, problem-centric approaches such as game-based learning. STEM competencies are an essential part of the educational response to the transformations caused by the fourth industrial revolution, spearheaded by the convergence of multiple exponential technologies. Teachers’ attitude is a critical success factor for any technology-enhanced learning innovation. This study explored in-service teachers’ views on the use of a digital educational escape room in virtual reality. Forty-one (n = 41) K-12 educators participated in a mixed research study involving a validated survey questionnaire instrument and an online debriefing session in the context of a teacher training program. The key findings revealed that such alternative instructional solutions can potentially enhance the cognitive benefits and learning outcomes, but further highlighted the shortcomings that instructional designers should consider while integrating them in contexts different than the intended. In line with this effort, more systematic professional development actions are recommended to encourage the development of additional teacher-led interventions. Full article
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Article
Automatic Hemiplegia Type Detection (Right or Left) Using the Levenberg-Marquardt Backpropagation Method
Information 2022, 13(2), 101; https://doi.org/10.3390/info13020101 - 21 Feb 2022
Viewed by 645
Abstract
Hemiplegia affects a significant portion of the human population. It is a condition that causes motor impairment and severely reduces the patient’s quality of life. This paper presents an automatic system for identifying the hemiplegia type (right or left part of the body [...] Read more.
Hemiplegia affects a significant portion of the human population. It is a condition that causes motor impairment and severely reduces the patient’s quality of life. This paper presents an automatic system for identifying the hemiplegia type (right or left part of the body is affected). The proposed system utilizes the data taken from patients and healthy subjects using the accelerometer sensor from the RehaGait mobile gait analysis system. The collected data undergo a pre-processing procedure followed by a feature extraction stage. The extracted features are then sent to a neural network trained by the Levenberg-Marquardt backpropagation (LM-BP) algorithm. The experimental part of this research involved creating a custom-created dataset containing entries taken from ten healthy and twenty non-healthy subjects. The data were taken from seven different sensors placed in specific areas of the subjects’ bodies. These sensors can capture a three-dimensional (3D) signal using the accelerometer, magnetometer, and gyroscope device types. The proposed system used the signals taken from the accelerometers, which were split into 2-sec windows. The proposed system achieved a classification accuracy of 95.12% and was compared with fourteen commonly used machine learning approaches. Full article
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