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Computers, Volume 10, Issue 10 (October 2021) – 16 articles

Cover Story (view full-size image): Increased consumer requirements for quality, safety, and traceability of goods, especially in food supply chains, has accelerated the implementation of blockchain during the COVID-19 pandemic. The right choice of blockchain software in agriculture is a complicated task and an important prerequisite for successful deployment. In this study, we propose a conceptual framework for group multicriteria selection of blockchain software in a fuzzy environment according to organization needs and experts’ judgements. The applicability of the new framework has been verified through an illustrative example for ranking blockchain systems. The evaluations of compared alternatives were calculated by using a fuzzy measurement of alternatives and ranking according to the compromise solution (MARCOS) model with different sets of weight coefficients. View this paper
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16 pages, 20460 KiB  
Article
Ready Teacher One: Virtual and Augmented Reality Online Professional Development for K-12 School Teachers
by Stylianos Mystakidis, Maria Fragkaki and Giorgos Filippousis
Computers 2021, 10(10), 134; https://doi.org/10.3390/computers10100134 - 17 Oct 2021
Cited by 39 | Viewed by 9455
Abstract
Augmented reality (AR) and virtual reality (VR) are two technologies with the potential to enhance learning quality by activating episodic student memory. In this manuscript we outline the pedagogical benefits of AR and VR as well as the rationale, design, development, and pilot [...] Read more.
Augmented reality (AR) and virtual reality (VR) are two technologies with the potential to enhance learning quality by activating episodic student memory. In this manuscript we outline the pedagogical benefits of AR and VR as well as the rationale, design, development, and pilot evaluation results from an in-service teacher online professional development program (OPD) on AR and VR linked with research activities. More specifically, we examined the “Augmented and Virtual Reality in Teaching and Learning” OPD course aimed at K-12 educators in a European country combining pedagogically informed methods such as inquiry-based learning and digital storytelling. Findings from a mixed-method research using questionnaires and focus groups indicate that AR- and VR-based pedagogical scenarios can be integrated effectively into everyday school teaching practice. The study also outlines implications and limitations that policy makers, education leaders, and educators need to consider for efficient institution-wide deployment of AR and VR technologies. Full article
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17 pages, 2532 KiB  
Article
Combining Blockchains, Smart Contracts, and Complex Sensors Management Platform for Hyper-Connected SmartCities: An IoT Data Marketplace Use Case
by Georgios Palaiokrassas, Petros Skoufis, Orfefs Voutyras, Takafumi Kawasaki, Mathieu Gallissot, Radhouene Azzabi, Akira Tsuge, Antonios Litke, Tadashi Okoshi, Jin Nakazawa and Theodora Varvarigou
Computers 2021, 10(10), 133; https://doi.org/10.3390/computers10100133 - 16 Oct 2021
Cited by 13 | Viewed by 4638
Abstract
In this paper, we demonstrate the multiple points of innovation when combining blockchain technology with Internet of Things (IoT) and security frameworks. The deployment and use of IoT device networks in smart city environments has produced an enormous amount of data. The fact [...] Read more.
In this paper, we demonstrate the multiple points of innovation when combining blockchain technology with Internet of Things (IoT) and security frameworks. The deployment and use of IoT device networks in smart city environments has produced an enormous amount of data. The fact that those data are possessed by multiple sources that use independent systems for data collection, storage, and use impedes the exploitation of their value. Blockchains, as distributed ledgers, can be used for addressing the development of a universal system for data collection and distribution. Smart contracts can be used to automate all the processes of such a network, while at the same time, blockchain and the InterPlanetary File System (IPFS) protect sensitive data through anonymity and distributed storage. An innovative and open IoT blockchain market of applications, data, and services is proposed that: (i) provides the framework upon which objects and people can exchange value in form of virtual currencies, for assets (data and services) received; (ii) defines the motivation incentives according to social and business context for humans and smart objects to interact. The specific marketplace is piloted through a cross-border trial between Santander and Fujisawa, in the context of the M-Sec project, validating thus the interoperability, efficiency, and data protection principles. Full article
(This article belongs to the Special Issue Edge and Cloud Computing in IoT)
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24 pages, 33634 KiB  
Article
Gamification as a Strategy to Increase Motivation and Engagement in Higher Education Chemistry Students
by Guillermo M. Chans and May Portuguez Castro
Computers 2021, 10(10), 132; https://doi.org/10.3390/computers10100132 - 16 Oct 2021
Cited by 73 | Viewed by 22475
Abstract
In the last year, educational experiences have become increasingly challenging due to teaching classes remotely. For this reason, it has been necessary to develop educational strategies that accompany the use of new technologies to maintain student interest. One of these methodologies is gamification, [...] Read more.
In the last year, educational experiences have become increasingly challenging due to teaching classes remotely. For this reason, it has been necessary to develop educational strategies that accompany the use of new technologies to maintain student interest. One of these methodologies is gamification, implemented in school environments more frequently due to the pandemic and whose impact on student motivation and engagement needs to be explored. The literature shows that student participation in these contexts should be increased when applying this methodology, where teachers can also provide greater support. This research proposes improving these aspects by developing a gamification strategy that can be easily replicated in other environments. This study was carried out for a chemistry course at a university in central Mexico. This proposal details the short-, medium-, and long-term bonuses which stimulated and motivated students and achieved specific objectives. We also present the quantitative results of a questionnaire applied to 48 engineering students to identify their perceptions of how gamification could increase motivation and engagement in learning the subject of chemistry. In addition, pre- and post-knowledge tests were applied to determine whether there were changes in the learning outcomes. The results indicated that gamification increased student motivation and engagement, improved attitudes, promoted actions such as keeping the camera on during lectures and regular attendance, and improved student grades. This study fills the need for planning strategies to help improve student motivation in online classes and proposes an instrument to measure the results. It can be helpful to those interested in applying or adapting it in other disciplines. Full article
(This article belongs to the Special Issue Interactive Technology and Smart Education)
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18 pages, 1168 KiB  
Article
A Methodology for Generating Systems Architectural Glimpse Statements Using the 5W1H Maxim
by Orfefs Voutyras, Aamir H. Bokhari, Akira Tsuge, Georgios Palaiokrassas, Takafumi Kawasaki, Xavier Cases-Camats, Jin Nakazawa, Antonios Litke, Tadashi Okoshi and Theodora Varvarigou
Computers 2021, 10(10), 131; https://doi.org/10.3390/computers10100131 - 15 Oct 2021
Cited by 1 | Viewed by 3985
Abstract
Attempts to facilitate and streamline systems architecting have resulted in a great number of reusable principles, practices, mechanisms, frameworks, and tools. Such a practice is the use of architectural viewpoints and views. However, as systems change, these practices should also evolve. The increasing [...] Read more.
Attempts to facilitate and streamline systems architecting have resulted in a great number of reusable principles, practices, mechanisms, frameworks, and tools. Such a practice is the use of architectural viewpoints and views. However, as systems change, these practices should also evolve. The increasing scale and complexity of systems resulting from an ever-growing pool of human needs and breakthroughs may lead, in some cases, to an increased gap between the abstraction activities attempting to capture the whole of a system, and the instantiation activities that produce concrete and detailed descriptions of a system’s architecture. To address this issue, this article introduces a new notion, that of architectural glimpse statements, fundamental questions acting as the building blocks for architectural views and products. This notion can help architects ask the right questions in the right manner to create fundamental statements, the elaboration on which can lead directly to concrete architectural products. Working on top of standardized and common approaches, the article introduces a language for the creation of architectural glimpse statements using the 5W1H maxim. Based on this language, a tool and guidelines are also provided to facilitate the usage of glimpses. Finally, the overall methodology is demonstrated in two case studies. Full article
(This article belongs to the Special Issue Edge and Cloud Computing in IoT)
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21 pages, 746 KiB  
Review
IoT Serverless Computing at the Edge: A Systematic Mapping Review
by Vojdan Kjorveziroski, Sonja Filiposka and Vladimir Trajkovik
Computers 2021, 10(10), 130; https://doi.org/10.3390/computers10100130 - 15 Oct 2021
Cited by 26 | Viewed by 4729
Abstract
Serverless computing is a new concept allowing developers to focus on the core functionality of their code, while abstracting away the underlying infrastructure. Even though there are existing commercial serverless cloud providers and open-source solutions, dealing with the explosive growth of new Internet [...] Read more.
Serverless computing is a new concept allowing developers to focus on the core functionality of their code, while abstracting away the underlying infrastructure. Even though there are existing commercial serverless cloud providers and open-source solutions, dealing with the explosive growth of new Internet of Things (IoT) devices requires more efficient bandwidth utilization, reduced latency, and data preprocessing closer to the source, thus reducing the overall data volume and meeting privacy regulations. Moving serverless computing to the edge of the network is a topic that is actively being researched with the aim of solving these issues. This study presents a systematic mapping review of current progress made to this effect, analyzing work published between 1 January 2015 and 1 September 2021. Using a document selection methodology which emphasizes the quality of the papers obtained through querying several popular databases with relevant search terms, we have included 64 entries, which we then further categorized into eight main categories. Results show that there is an increasing interest in this area with rapid progress being made to solve the remaining open issues, which have also been summarized in this paper. Special attention is paid to open-source efforts, as well as open-access contributions. Full article
(This article belongs to the Special Issue Edge Computing for the IoT)
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27 pages, 9723 KiB  
Article
A Novel Multi-Modality Image Simultaneous Denoising and Fusion Method Based on Sparse Representation
by Guanqiu Qi, Gang Hu, Neal Mazur, Huahua Liang and Matthew Haner
Computers 2021, 10(10), 129; https://doi.org/10.3390/computers10100129 - 13 Oct 2021
Cited by 9 | Viewed by 2220
Abstract
Multi-modality image fusion applied to improve image quality has drawn great attention from researchers in recent years. However, noise is actually generated in images captured by different types of imaging sensors, which can seriously affect the performance of multi-modality image fusion. As the [...] Read more.
Multi-modality image fusion applied to improve image quality has drawn great attention from researchers in recent years. However, noise is actually generated in images captured by different types of imaging sensors, which can seriously affect the performance of multi-modality image fusion. As the fundamental method of noisy image fusion, source images are denoised first, and then the denoised images are fused. However, image denoising can decrease the sharpness of source images to affect the fusion performance. Additionally, denoising and fusion are processed in separate processing modes, which causes an increase in computation cost. To fuse noisy multi-modality image pairs accurately and efficiently, a multi-modality image simultaneous fusion and denoising method is proposed. In the proposed method, noisy source images are decomposed into cartoon and texture components. Cartoon-texture decomposition not only decomposes source images into detail and structure components for different image fusion schemes, but also isolates image noise from texture components. A Gaussian scale mixture (GSM) based sparse representation model is presented for the denoising and fusion of texture components. A spatial domain fusion rule is applied to cartoon components. The comparative experimental results confirm the proposed simultaneous image denoising and fusion method is superior to the state-of-the-art methods in terms of visual and quantitative evaluations. Full article
(This article belongs to the Special Issue Feature Paper in Computers)
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23 pages, 2789 KiB  
Article
Ontology-Based Reasoning for Educational Assistance in Noncommunicable Chronic Diseases
by Andrêsa Vargas Larentis, Eduardo Gonçalves de Azevedo Neto, Jorge Luis Victória Barbosa, Débora Nice Ferrari Barbosa, Valderi Reis Quietinho Leithardt and Sérgio Duarte Correia
Computers 2021, 10(10), 128; https://doi.org/10.3390/computers10100128 - 12 Oct 2021
Cited by 5 | Viewed by 2542
Abstract
Noncommunicable chronic diseases (NCDs) affect a large part of the population. With the emergence of COVID-19, its most severe cases impact people with NCDs, increasing the mortality rate. For this reason, it is necessary to develop personalized solutions to support healthcare considering the [...] Read more.
Noncommunicable chronic diseases (NCDs) affect a large part of the population. With the emergence of COVID-19, its most severe cases impact people with NCDs, increasing the mortality rate. For this reason, it is necessary to develop personalized solutions to support healthcare considering the specific characteristics of individuals. This paper proposes an ontology to represent the knowledge of educational assistance in NCDs. The purpose of ontology is to support educational practices and systems oriented towards preventing and monitoring these diseases. The ontology is implemented under Protégé 5.5.0 in Ontology Web Language (OWL) format, and defined competency questions, SWRL rules, and SPARQL queries. The current version of ontology includes 138 classes, 31 relations, 6 semantic rules, and 575 axioms. The ontology serves as a NCDs knowledge base and supports automatic reasoning. Evaluations performed through a demo dataset demonstrated the effectiveness of the ontology. SWRL rules were used to define accurate axioms, improving the correct classification and inference of six instantiated individuals. As a scientific contribution, this study presents the first ontology for educational assistance in NCDs. Full article
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24 pages, 12397 KiB  
Article
IoTSAS: An Integrated System for Real-Time Semantic Annotation and Interpretation of IoT Sensor Stream Data
by Besmir Sejdiu, Florije Ismaili and Lule Ahmedi
Computers 2021, 10(10), 127; https://doi.org/10.3390/computers10100127 - 11 Oct 2021
Cited by 8 | Viewed by 3170
Abstract
Sensors and other Internet of Things (IoT) technologies are increasingly finding application in various fields, such as air quality monitoring, weather alerts monitoring, water quality monitoring, healthcare monitoring, etc. IoT sensors continuously generate large volumes of observed stream data; therefore, processing requires a [...] Read more.
Sensors and other Internet of Things (IoT) technologies are increasingly finding application in various fields, such as air quality monitoring, weather alerts monitoring, water quality monitoring, healthcare monitoring, etc. IoT sensors continuously generate large volumes of observed stream data; therefore, processing requires a special approach. Extracting the contextual information essential for situational knowledge from sensor stream data is very difficult, especially when processing and interpretation of these data are required in real time. This paper focuses on processing and interpreting sensor stream data in real time by integrating different semantic annotations. In this context, a system named IoT Semantic Annotations System (IoTSAS) is developed. Furthermore, the performance of the IoTSAS System is presented by testing air quality and weather alerts monitoring IoT domains by extending the Open Geospatial Consortium (OGC) standards and the Sensor Observations Service (SOS) standards, respectively. The developed system provides information in real time to citizens about the health implications from air pollution and weather conditions, e.g., blizzard, flurry, etc. Full article
(This article belongs to the Special Issue Real-Time Systems in Emerging IoT-Embedded Applications)
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14 pages, 4395 KiB  
Article
Developing Physics Experiments Using Augmented Reality Game-Based Learning Approach: A Pilot Study in Primary School
by Maria Zafeiropoulou, Christina Volioti, Euclid Keramopoulos and Theodosios Sapounidis
Computers 2021, 10(10), 126; https://doi.org/10.3390/computers10100126 - 11 Oct 2021
Cited by 16 | Viewed by 4156
Abstract
The augmented reality game-based learning (ARGBL) approach is an advantageous pathway for the development and enhancement of teaching and learning processes. To this end, this paper presents the design and development of an ARGBL application for the implementation of physics experiments in the [...] Read more.
The augmented reality game-based learning (ARGBL) approach is an advantageous pathway for the development and enhancement of teaching and learning processes. To this end, this paper presents the design and development of an ARGBL application for the implementation of physics experiments in the fifth grade of a Greek primary school. The purpose of the ARGBL system is twofold: to educate and entertain. For this reason, a treasure hunt game was implemented, which allows students to interact with a digital world and to manipulate virtual objects with the use of an augmented reality (AR) device. Then, according to the instructions, students have to collect all the materials to conduct the AR educational experiment. Overall, the evaluation of the system’s usability by 17 users (both students and teachers) was very promising, indicating that the ARGBL application has the potential to be an easy-to-use educational tool for improving not only the teaching of physics experiments in primary school but also the learning process, by positively affecting the students’ motivation and engagement. Full article
(This article belongs to the Special Issue Game-Based Learning, Gamification in Education and Serious Games)
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19 pages, 673 KiB  
Article
Invariant-Based Safety Assessment of FPGA Projects: Conception and Technique
by Vyacheslav Kharchenko, Oleg Illiashenko and Vladimir Sklyar
Computers 2021, 10(10), 125; https://doi.org/10.3390/computers10100125 - 10 Oct 2021
Cited by 3 | Viewed by 2580
Abstract
This paper describes a proposed method and technology of safety assessment of projects based on field programmable gate arrays (FPGA). Safety assessment is based on special invariants, e.g., properties which remain unchanged when a specified transformation is applied. A classification and examples of [...] Read more.
This paper describes a proposed method and technology of safety assessment of projects based on field programmable gate arrays (FPGA). Safety assessment is based on special invariants, e.g., properties which remain unchanged when a specified transformation is applied. A classification and examples of FPGA project invariants are provided. In the paper, two types of invariants are described. The first type of invariants used for such assessment are those which are versatile since they reflect the unchanged properties of FPGA projects, hardware description languages, etc. These invariants can be replenished as experience gained in project implementation accumulates. The second type of invariants is formed based on an analysis of the specifics of a particular FPGA project and reflects the features of the tasks to be solved, the algorithms that are implemented, the hardware FPGA chips used, and the computer-aided design tools, etc. The paper contains a description of the overall conception and particular stages of FPGA projects invariant-based safety assessment. As examples for solving some tasks (using of invariants and defect injections), the paper contains several algorithms written in the VHSIC hardware description language (VHDL). The paper summarizes the results obtained during several years of practical and theoretical research. It can be of practical use for engineers and researchers in the field of quality, reliability, and security of embedded systems, software and information management systems for critical and business applications. Full article
(This article belongs to the Special Issue Real-Time Systems in Emerging IoT-Embedded Applications)
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17 pages, 667 KiB  
Article
Black-Hole Optimization Applied to the Parametric Estimation in Distribution Transformers Considering Voltage and Current Measures
by Camilo Andres Arenas-Acuña, Jonathan Andres Rodriguez-Contreras, Oscar Danilo Montoya and Edwin Rivas-Trujillo
Computers 2021, 10(10), 124; https://doi.org/10.3390/computers10100124 - 9 Oct 2021
Cited by 13 | Viewed by 2409
Abstract
The problem of parametric estimation in single-phase transformers is addressed in this research from the point of view of metaheuristic optimization. The parameters of interest are the series resistance and reactance as well as the magnetization resistance and reactance. To obtain these parameters [...] Read more.
The problem of parametric estimation in single-phase transformers is addressed in this research from the point of view of metaheuristic optimization. The parameters of interest are the series resistance and reactance as well as the magnetization resistance and reactance. To obtain these parameters considering only the voltage and the currents measured in the terminals of the transformer, a nonlinear optimization model that deals with the minimization of the mean square error among the measured and calculated voltage and current variables is formulated. The nonlinear programming model is solved through the implementation of a simple but efficient metaheuristic optimization technique known as the black-hole optimizer. Numerical simulations demonstrate that the proposed optimization method allows for the reduction in the estimation error among the measured and calculated variables when compared with methods that are well established in the literature such as particle swarm optimization and genetic algorithms, among others. All the simulations were carried out in the MATLAB programming environment. Full article
(This article belongs to the Special Issue Computing, Electrical and Industrial Systems 2021)
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17 pages, 1305 KiB  
Article
Recommendation Algorithm Using Clustering-Based UPCSim (CB-UPCSim)
by Triyanna Widiyaningtyas, Indriana Hidayah and Teguh Bharata Adji
Computers 2021, 10(10), 123; https://doi.org/10.3390/computers10100123 - 6 Oct 2021
Cited by 10 | Viewed by 2893
Abstract
One of the well-known recommendation systems is memory-based collaborative filtering that utilizes similarity metrics. Recently, the similarity metrics have taken into account the user rating and user behavior scores. The user behavior score indicates the user preference in each product type (genre). The [...] Read more.
One of the well-known recommendation systems is memory-based collaborative filtering that utilizes similarity metrics. Recently, the similarity metrics have taken into account the user rating and user behavior scores. The user behavior score indicates the user preference in each product type (genre). The added user behavior score to the similarity metric results in more complex computation. To reduce the complex computation, we combined the clustering method and user behavior score-based similarity. The clustering method applies k-means clustering by determination of the number of clusters using the Silhouette Coefficient. Whereas the user behavior score-based similarity utilizes User Profile Correlation-based Similarity (UPCSim). The experimental results with the MovieLens 100k dataset showed a faster computation time of 4.16 s. In addition, the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) values decreased by 1.88% and 1.46% compared to the baseline algorithm. Full article
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23 pages, 464 KiB  
Article
Analytical and Numerical Evaluation of Co-Scheduling Strategies and Their Application
by Ruslan Kuchumov and Vladimir Korkhov
Computers 2021, 10(10), 122; https://doi.org/10.3390/computers10100122 - 2 Oct 2021
Cited by 2 | Viewed by 1950
Abstract
Applications in high-performance computing (HPC) may not use all available computational resources, leaving some of them underutilized. By co-scheduling, i.e., running more than one application on the same computational node, it is possible to improve resource utilization and overall throughput. Some applications may [...] Read more.
Applications in high-performance computing (HPC) may not use all available computational resources, leaving some of them underutilized. By co-scheduling, i.e., running more than one application on the same computational node, it is possible to improve resource utilization and overall throughput. Some applications may have conflicting requirements on resources and co-scheduling may cause performance degradation, so it is important to take it into account in scheduling decisions. In this paper, we formalize the co-scheduling problem and propose multiple scheduling strategies to solve it: an optimal strategy, an online strategy and heuristic strategies. These strategies vary in terms of the optimality of the solution they produce and a priori information about the system they require. We show theoretically that the online strategy provides schedules with a competitive ratio that has a constant upper limit. This allows us to solve the co-scheduling problem using heuristic strategies that approximate this online strategy. Numerical simulations show how heuristic strategies compare to the optimal strategy for different input systems. We propose a method for measuring input parameters of the model in practice and evaluate this method on HPC benchmark applications. We show the high accuracy of the measurement method, which allows us to apply the proposed scheduling strategies in the scheduler implementation. Full article
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22 pages, 1818 KiB  
Review
Fraud Detection Using the Fraud Triangle Theory and Data Mining Techniques: A Literature Review
by Marco Sánchez-Aguayo, Luis Urquiza-Aguiar and José Estrada-Jiménez
Computers 2021, 10(10), 121; https://doi.org/10.3390/computers10100121 - 30 Sep 2021
Cited by 21 | Viewed by 18513
Abstract
Fraud entails deception in order to obtain illegal gains; thus, it is mainly evidenced within financial institutions and is a matter of general interest. The problem is particularly complex, since perpetrators of fraud could belong to any position, from top managers to payroll [...] Read more.
Fraud entails deception in order to obtain illegal gains; thus, it is mainly evidenced within financial institutions and is a matter of general interest. The problem is particularly complex, since perpetrators of fraud could belong to any position, from top managers to payroll employees. Fraud detection has traditionally been performed by auditors, who mainly employ manual techniques. These could take too long to process fraud-related evidence. Data mining, machine learning, and, as of recently, deep learning strategies are being used to automate this type of processing. Many related techniques have been developed to analyze, detect, and prevent fraud-related behavior, with the fraud triangle associated with the classic auditing model being one of the most important of these. This work aims to review current work related to fraud detection that uses the fraud triangle in addition to machine learning and deep learning techniques. We used the Kitchenham methodology to analyze the research works related to fraud detection from the last decade. This review provides evidence that fraud is an area of active investigation. Several works related to fraud detection using machine learning techniques were identified without the evidence that they incorporated the fraud triangle as a method for more efficient analysis. Full article
(This article belongs to the Special Issue Artificial Intelligence for Digital Humanities (AI4DH))
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24 pages, 557 KiB  
Article
Blockchain Software Selection as a Fuzzy Multi-Criteria Problem
by Galina Ilieva, Tania Yankova, Irina Radeva and Ivan Popchev
Computers 2021, 10(10), 120; https://doi.org/10.3390/computers10100120 - 24 Sep 2021
Cited by 22 | Viewed by 4441
Abstract
Increased consumer requirements for quality, safety and traceability of goods in supply chains has accelerated the implementation of blockchain during the COVID-19 pandemic. The right choice of blockchain software is a complicated task and an important prerequisite for successful deployment. In this study, [...] Read more.
Increased consumer requirements for quality, safety and traceability of goods in supply chains has accelerated the implementation of blockchain during the COVID-19 pandemic. The right choice of blockchain software is a complicated task and an important prerequisite for successful deployment. In this study, we propose a conceptual framework for group multi-criteria selection of blockchain software in fuzzy environment according to organization needs and experts’ judgements. The applicability of the new framework has been verified through an illustrative example for ranking blockchain systems. The evaluations of compared alternatives were calculated by using measurement of alternatives and ranking according to the compromise solution (MARCOS) method. The robustness of the new framework was proven by sensitivity analysis in which two (crisp and fuzzy) MARCOS models with two different sets of weighting coefficients were compared. Full article
(This article belongs to the Special Issue Cloud Computing Security and Blockchain Technology)
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22 pages, 26301 KiB  
Article
A Novel Simulation Platform for Underwater Data Muling Communications Using Autonomous Underwater Vehicles
by Filipe B. Teixeira, Bruno M. Ferreira, Nuno Moreira, Nuno Abreu, Murillo Villa, João P. Loureiro, Nuno A. Cruz, José C. Alves, Manuel Ricardo and Rui Campos
Computers 2021, 10(10), 119; https://doi.org/10.3390/computers10100119 - 22 Sep 2021
Cited by 5 | Viewed by 3259
Abstract
Autonomous Underwater Vehicles (AUVs) are seen as a safe and cost-effective platforms for performing a myriad of underwater missions. These vehicles are equipped with multiple sensors which, combined with their long endurance, can produce large amounts of data, especially when used for video [...] Read more.
Autonomous Underwater Vehicles (AUVs) are seen as a safe and cost-effective platforms for performing a myriad of underwater missions. These vehicles are equipped with multiple sensors which, combined with their long endurance, can produce large amounts of data, especially when used for video capturing. These data need to be transferred to the surface to be processed and analyzed. When considering deep sea operations, where surfacing before the end of the mission may be unpractical, the communication is limited to low bitrate acoustic communications, which make unfeasible the timely transmission of large amounts of data unfeasible. The usage of AUVs as data mules is an alternative communications solution. Data mules can be used to establish a broadband data link by combining short-range, high bitrate communications (e.g., RF and wireless optical) with a Delay Tolerant Network approach. This paper presents an enhanced version of UDMSim, a novel simulation platform for data muling communications. UDMSim is built upon a new realistic AUV Motion and Localization (AML) simulator and Network Simulator 3 (ns-3). It can simulate the position of the data mules, including localization errors, realistic position control adjustments, the received signal, the realistic throughput adjustments, and connection losses due to the fast SNR change observed underwater. The enhanced version includes a more realistic AML simulator and the antenna radiation patterns to help evaluating the design and relative placement of underwater antennas. The results obtained using UDMSim show a good match with the experimental results achieved using an underwater testbed. UDMSim is made available to the community to support easy and faster evaluation of underwater data muling oriented communications solutions and to enable offline replication of real world experiments. Full article
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