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Computers, Volume 10, Issue 12 (December 2021) – 16 articles

Cover Story (view full-size image): Web browsers are one of the most used applications on every computational device. Hence, they play a pivotal role in any forensic investigation and help to determine if nefarious or suspicious activity has occurred on that device. Our study investigates the use of private mode and browsing artefacts within four web browsers and focuses on analyzing both hard disk and random-access memory. Forensic analysis on the browsing activity, search history, cookies, and temporary files of the target device showed that using the private mode artefacts are not saved in the device’s hard disks and matched each web browser vendors’ claims; however, in volatile memory analysis, most artefacts were retrieved. View this paper
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Article
A Lightweight BPMN Extension for Business Process-Oriented Requirements Engineering
Computers 2021, 10(12), 171; https://doi.org/10.3390/computers10120171 - 16 Dec 2021
Cited by 1 | Viewed by 900
Abstract
Process-oriented requirements engineering approaches are often required to deal with the effective adaptation of existing processes in order to easily introduce new or updated requirements. Such approaches are based on the adoption of widely used notations, such as the one introduced by the [...] Read more.
Process-oriented requirements engineering approaches are often required to deal with the effective adaptation of existing processes in order to easily introduce new or updated requirements. Such approaches are based on the adoption of widely used notations, such as the one introduced by the Business Process Model and Notation (BPMN) standard. However, BPMN models do not convey enough information on the involved entities and how they interact with process activities, thus leading to ambiguities, as well as to incomplete and inconsistent requirements definitions. This paper proposes an approach that allows stakeholders and software analysts to easily merge and integrate behavioral and data properties in a BPMN model, so as to fully exploit the potential of BPMN without incurring into the aforementioned limitation. The proposed approach introduces a lightweight BPMN extension that specifically addresses the annotation of data properties in terms of constraints, i.e., pre- and post-conditions that the different process activities must satisfy. The visual representation of the annotated model conveys all the information required both by stakeholders, to understand and validate requirements, and by software analysts and developers, to easily map these updates to the corresponding software implementation. The presented approach is illustrated by use of two running examples, which have also been used to carry out a preliminary validation activity. Full article
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Article
LENNA (Learning Emotions Neural Network Assisted): An Empathic Chatbot Designed to Study the Simulation of Emotions in a Bot and Their Analysis in a Conversation
Computers 2021, 10(12), 170; https://doi.org/10.3390/computers10120170 - 13 Dec 2021
Viewed by 1035
Abstract
Currently, most chatbots are unable to detect the emotional state of the interlocutor and respond according to the interlocutor’s emotional state. Over the last few years, there has been growing interest in empathic chatbots. In other disciplines aside from artificial intelligence, e.g., in [...] Read more.
Currently, most chatbots are unable to detect the emotional state of the interlocutor and respond according to the interlocutor’s emotional state. Over the last few years, there has been growing interest in empathic chatbots. In other disciplines aside from artificial intelligence, e.g., in medicine, there is growing interest in the study and simulation of human emotions. However, there is a fundamental issue that is not commonly addressed, and it is the design of protocols for quantitatively evaluating an empathic chatbot by utilizing the analysis of the conversation between the bot and an interlocutor. This study is motivated by the aforementioned scenarios and by the lack of methods for assessing the performance of an empathic bot; thus, a chatbot with the ability to recognize the emotions of its interlocutor is needed. The main novelty of this study is the protocol with which it is possible to analyze the conversations between a chatbot and an interlocutor, regardless of whether the latter is a person or another chatbot. For this purpose, we have designed a minimally viable prototype of an empathic chatbot, named LENNA, for evaluating the usefulness of the proposed protocol. The proposed approach uses Shannon entropy to measure the changes in the emotional state experienced by the chatbot during a conversation, applying sentiment analysis techniques to the analysis of the conversation. Once the simulation experiments were performed, the conversations were analyzed by applying multivariate statistical methods and Fourier analysis. We show the usefulness of the proposed methodology for evaluating the emotional state of LENNA during conversations, which could be useful in the evaluation of other empathic chatbots. Full article
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Article
An Applying Colored Petri Net for Computerized Accounting System and Ledger Accounts Instruction
Computers 2021, 10(12), 169; https://doi.org/10.3390/computers10120169 - 12 Dec 2021
Viewed by 979
Abstract
Many learners who are not familiar with the accounting terms find blended learning very complex to understand with respect to the computerized accounting system, the journal entries process, and tracing the accounting transaction flows of accounting system. A simulation-based model is a viable [...] Read more.
Many learners who are not familiar with the accounting terms find blended learning very complex to understand with respect to the computerized accounting system, the journal entries process, and tracing the accounting transaction flows of accounting system. A simulation-based model is a viable option to help instructors and learners make understanding the accounting system components and monitoring the accounting transactions easier. This paper proposes a colored Petri net (CPN)-based model for the instruction of an accounting system focused on the journal entries processes, accounting modules, and accounting transaction flows. The CPN-based language and the model checking tool named CPN are used to represent the accounting system components: a chart of accounts, an account mapping profile, the journal and ledgers system, and the financial report creations. We evaluated the designed CPN models by creating the simulation cases from ground truth data of the retail department store system and the mortgage loan system, using the decision-table-based testing technique. The results show that the designed CPN model and provided simulation cases help the learners to animate, verify, trace back accounting transactions and data flows, and increase the learner’s understanding. Full article
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Review
The Use of Blockchain Technology in e-Government Services
Computers 2021, 10(12), 168; https://doi.org/10.3390/computers10120168 - 10 Dec 2021
Cited by 3 | Viewed by 1487
Abstract
e-Government services have evolved significantly over the last decade, from a paper-based bureaucratic procedure to digital services. Electronically processed transactions require limited physical interaction with the public administration, and provide reduced response times, increased transparency, confidentiality and integrity. Blockchain technology enhances many of [...] Read more.
e-Government services have evolved significantly over the last decade, from a paper-based bureaucratic procedure to digital services. Electronically processed transactions require limited physical interaction with the public administration, and provide reduced response times, increased transparency, confidentiality and integrity. Blockchain technology enhances many of the above properties as it facilitates immutability and transparency for the recorded transactions and can help establish trust among participants. In this paper, we conduct a literature review on the use of blockchain technology in e-government applications to identify e-government services that can benefit from the use of blockchains, types of technologies that are chosen for the proposed solutions, and their corresponding maturity levels. The aim is to demonstrate blockchain’s potential and contribution to the field, provide useful insights to governments who are considering investing in this innovative technology, and facilitate researchers in their future activities in blockchain-enabled e-government services. Full article
(This article belongs to the Special Issue Blockchain-Based Systems)
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Article
Assessment of Sustainable Collaboration in Collaborative Business Ecosystems
Computers 2021, 10(12), 167; https://doi.org/10.3390/computers10120167 - 06 Dec 2021
Viewed by 1006
Abstract
Advances in information and communication technologies and, more specifically, in artificial intelligence resulted in more intelligent systems, which, in the business world, particularly in collaborative business ecosystems, can lead to a more streamlined, effective, and sustainable processes. Following the design science research method, [...] Read more.
Advances in information and communication technologies and, more specifically, in artificial intelligence resulted in more intelligent systems, which, in the business world, particularly in collaborative business ecosystems, can lead to a more streamlined, effective, and sustainable processes. Following the design science research method, this article presents a simulation model, which includes a performance assessment and influence mechanism to evaluate and influence the collaboration of the organisations in a business ecosystem. The establishment of adequate performance indicators to assess the organisations can act as an influencing factor of their behaviour, contributing to enhancing their performance and improving the ecosystem collaboration sustainability. As such, several scenarios are presented shaping the simulation model with actual data gathered from three IT industry organisations running in the same business ecosystem, assessed by a set of proposed performance indicators. The resulting outcomes show that the collaboration can be measured, and the organisations’ behaviour can be influenced by varying the weights of the performance indicators adopted by the CBE manager. Full article
(This article belongs to the Special Issue Computing, Electrical and Industrial Systems 2021)
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Article
Automated Paraphrase Quality Assessment Using Language Models and Transfer Learning
Computers 2021, 10(12), 166; https://doi.org/10.3390/computers10120166 - 06 Dec 2021
Viewed by 896
Abstract
Learning to paraphrase supports both writing ability and reading comprehension, particularly for less skilled learners. As such, educational tools that integrate automated evaluations of paraphrases can be used to provide timely feedback to enhance learner paraphrasing skills more efficiently and effectively. Paraphrase identification [...] Read more.
Learning to paraphrase supports both writing ability and reading comprehension, particularly for less skilled learners. As such, educational tools that integrate automated evaluations of paraphrases can be used to provide timely feedback to enhance learner paraphrasing skills more efficiently and effectively. Paraphrase identification is a popular NLP classification task that involves establishing whether two sentences share a similar meaning. Paraphrase quality assessment is a slightly more complex task, in which pairs of sentences are evaluated in-depth across multiple dimensions. In this study, we focus on four dimensions: lexical, syntactical, semantic, and overall quality. Our study introduces and evaluates various machine learning models using handcrafted features combined with Extra Trees, Siamese neural networks using BiLSTM RNNs, and pretrained BERT-based models, together with transfer learning from a larger general paraphrase corpus, to estimate the quality of paraphrases across the four dimensions. Two datasets are considered for the tasks involving paraphrase quality: ULPC (User Language Paraphrase Corpus) containing 1998 paraphrases and a smaller dataset with 115 paraphrases based on children’s inputs. The paraphrase identification dataset used for the transfer learning task is the MSRP dataset (Microsoft Research Paraphrase Corpus) containing 5801 paraphrases. On the ULPC dataset, our BERT model improves upon the previous baseline by at least 0.1 in F1-score across the four dimensions. When using fine-tuning from ULPC for the children dataset, both the BERT and Siamese neural network models improve upon their original scores by at least 0.11 F1-score. The results of these experiments suggest that transfer learning using generic paraphrase identification datasets can be successful, while at the same time obtaining comparable results in fewer epochs. Full article
(This article belongs to the Special Issue Feature Paper in Computers)
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Article
Browsers’ Private Mode: Is It What We Were Promised?
Computers 2021, 10(12), 165; https://doi.org/10.3390/computers10120165 - 02 Dec 2021
Viewed by 1536
Abstract
Web browsers are one of the most used applications on every computational device in our days. Hence, they play a pivotal role in any forensic investigation and help determine if nefarious or suspicious activity has occurred on that device. Our study investigates the [...] Read more.
Web browsers are one of the most used applications on every computational device in our days. Hence, they play a pivotal role in any forensic investigation and help determine if nefarious or suspicious activity has occurred on that device. Our study investigates the usage of private mode and browsing artefacts within four prevalent web browsers and is focused on analyzing both hard disk and random access memory. Forensic analysis on the target device showed that using private mode matched each of the web browser vendors’ claims, such as that browsing activity, search history, cookies and temporary files that are not saved in the device’s hard disks. However, in volatile memory analysis, a majority of artefacts within the test cases were retrieved. Hence, a malicious actor performing a similar approach could potentially retrieve sensitive information left behind on the device without the user’s consent. Full article
(This article belongs to the Special Issue Feature Paper in Computers)
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Article
Click Fraud in Digital Advertising: A Comprehensive Survey
Computers 2021, 10(12), 164; https://doi.org/10.3390/computers10120164 - 01 Dec 2021
Viewed by 1361
Abstract
Recent research has revealed an alarming prevalence of click fraud in online advertising systems. In this article, we present a comprehensive study on the usage and impact of bots in performing click fraud in the realm of digital advertising. Specifically, we first provide [...] Read more.
Recent research has revealed an alarming prevalence of click fraud in online advertising systems. In this article, we present a comprehensive study on the usage and impact of bots in performing click fraud in the realm of digital advertising. Specifically, we first provide an in-depth investigation of different known categories of Web-bots along with their malicious activities and associated threats. We then ask a series of questions to distinguish between the important behavioral characteristics of bots versus humans in conducting click fraud within modern-day ad platforms. Subsequently, we provide an overview of the current detection and threat mitigation strategies pertaining to click fraud as discussed in the literature, and we categorize the surveyed techniques based on which specific actors within a digital advertising system are most likely to deploy them. We also offer insights into some of the best-known real-world click bots and their respective ad fraud campaigns observed to date. According to our knowledge, this paper is the most comprehensive research study of its kind, as it examines the problem of click fraud both from a theoretical as well as practical perspective. Full article
(This article belongs to the Special Issue Feature Paper in Computers)
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Article
Implementation of Augmented Reality in a Mechanical Engineering Training Context
Computers 2021, 10(12), 163; https://doi.org/10.3390/computers10120163 - 29 Nov 2021
Cited by 1 | Viewed by 1050
Abstract
Global industry is at the heart of its fourth industrial revolution, being driven by the emergence of new digital solutions: Augmented reality allows us to consider the evolution towards the “the augmented operator”. This technology is currently little used in higher education, especially [...] Read more.
Global industry is at the heart of its fourth industrial revolution, being driven by the emergence of new digital solutions: Augmented reality allows us to consider the evolution towards the “the augmented operator”. This technology is currently little used in higher education, especially for mechanical engineers. We believe that it can facilitate learning and develop autonomy. The objective of this work is to assess the relevance of augmented reality in this context, as well as its impact on learning. The difficulties for a student approaching a technical system are related to reading and understanding 2D and even 3D representations, lack of knowledge on components functions, and the analysis of the chain of power transmission and transformation of movement. The research is intended to see if AR technologies are relevant to answer these issues and help beginners get started. To that end, several AR scenarios have been developed on different mechanical systems, using the relevant features of the AR interfaces that we have identified. Otherwise, these experiences have enabled us to identify specific issues linked to the implementation of AR. Our choice of AR devices and software allows us to have an integrated digital chain with digital tools and files used by mechanical engineers. Finally, we sought to assess how this technology made it possible to overcome the difficulties of learners, in different learning situations. Full article
(This article belongs to the Special Issue Xtended or Mixed Reality (AR+VR) for Education)
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Article
IoT Security Mechanisms in the Example of BLE
Computers 2021, 10(12), 162; https://doi.org/10.3390/computers10120162 - 29 Nov 2021
Viewed by 1122
Abstract
In recent years, a lot of IoT devices, wireless sensors, and smart things contain information that must be transmitted to the server for further processing. Due to the distance between devices, battery power, and the possibility of sudden device failure, the network that [...] Read more.
In recent years, a lot of IoT devices, wireless sensors, and smart things contain information that must be transmitted to the server for further processing. Due to the distance between devices, battery power, and the possibility of sudden device failure, the network that connects the devices must be scalable, energy efficient, and flexible. Particular attention must be paid to the protection of the transmitted data. The Bluetooth mesh was chosen as such a network. This network is built on top of Bluetooth Low-Energy devices, which are widespread in the market and whose radio modules are available from several manufacturers. This paper presents an overview of security mechanisms for the Bluetooth mesh network. This network provides encryption at two layers: network and upper transport layers, which increases the level of data security. The network uses sequence numbers for each message to protect against replay attacks. The introduction of devices into the network is provided with an encryption key, and the out-of-band (OOB) mechanism is also supported. At the moment, a comparison has been made between attacks and defense mechanisms that overlap these attacks. The article also suggested ways to improve network resiliency. Full article
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Article
A Systematic Modelling Procedure to Design Agent-Oriented Control to Coalition of Capabilities—In the Context of I4.0 as Virtual Assets (AAS)
Computers 2021, 10(12), 161; https://doi.org/10.3390/computers10120161 - 28 Nov 2021
Viewed by 1231
Abstract
Manufacturing systems need to meet Industry 4.0 (I4.0) guidelines to deal with uncertainty in scenarios of turbulent demand for products. The engineering concepts to define the service’s resources to manufacture the products will be more flexible, ensuring the possibility of re-planning in operation. [...] Read more.
Manufacturing systems need to meet Industry 4.0 (I4.0) guidelines to deal with uncertainty in scenarios of turbulent demand for products. The engineering concepts to define the service’s resources to manufacture the products will be more flexible, ensuring the possibility of re-planning in operation. These can follow the engineering paradigm based on capabilities. The virtualization of industry components and assets achieves the RAMI 4.0 guidelines and (I4.0C), which describes the Asset Administration Shell (AAS). However, AAS are passive components that provide information about I4.0 assets. The proposal of specific paradigms is exposed for managing these components, as is the case of multi-agent systems (MAS) that attribute intelligence to objects. The implementation of resource coalitions with evolutionary architectures (EAS) applies cooperation and capabilities’ association. Therefore, this work focuses on designing a method for modeling the asset administration shell (AAS) as virtual elements orchestrating intelligent agents (MAS) that attribute cooperation and negotiation through contracts to coalitions based on the engineering capabilities concept. The systematic method suggested in this work is partitioned for the composition of objects, AAS elements, and activities that guarantee the relationship between entities. Finally, Production Flow Schema (PFS) refinements are applied to generate the final Petri net models (PN) and validate them with Snoopy simulations. The results achieved demonstrate the validation of the procedure, eliminating interlocking and enabling liveliness to integrate elements’ behavior. Full article
(This article belongs to the Special Issue Computing, Electrical and Industrial Systems 2021)
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Review
Cloud-Based Business Process Security Risk Management: A Systematic Review, Taxonomy, and Future Directions
Computers 2021, 10(12), 160; https://doi.org/10.3390/computers10120160 - 26 Nov 2021
Cited by 1 | Viewed by 1202
Abstract
Despite the attractive benefits of cloud-based business processes, security issues, cloud attacks, and privacy are some of the challenges that prevent many organizations from using this technology. This review seeks to know the level of integration of security risk management process at each [...] Read more.
Despite the attractive benefits of cloud-based business processes, security issues, cloud attacks, and privacy are some of the challenges that prevent many organizations from using this technology. This review seeks to know the level of integration of security risk management process at each phase of the Business Process Life Cycle (BPLC) for securing cloud-based business processes; usage of an existing risk analysis technique as the basis of risk assessment model, usage of security risk standard, and the classification of cloud security risks in a cloud-based business process. In light of these objectives, this study presented an exhaustive review of the current state-of-the-art methodology for managing cloud-based business process security risk. Eleven electronic databases (ACM, IEEE, Science Direct, Google Scholar, Springer, Wiley, Taylor and Francis, IEEE cloud computing Conference, ICSE conference, COMPSAC conference, ICCSA conference, Computer Standards and Interfaces Journal) were used for the selected publications. A total of 1243 articles were found. After using the selection criteria, 93 articles were selected, while 17 articles were found eligible for in-depth evaluation. For the results of the business process lifecycle evaluation, 17% of the approaches integrated security risk management into one of the phases of the business process, while others did not. For the influence of the results of the domain assessment of risk management, three key indicators (domain applicability, use of existing risk management techniques, and integration of risk standards) were used to substantiate our findings. The evaluation result of domain applicability showed that 53% of the approaches had been testing run in real-time, thereby making these works reusable. The result of the usage of existing risk analysis showed that 52.9% of the authors implemented their work using existing risk analysis techniques while 29.4% of the authors partially integrated security risk standards into their work. Based on these findings and results, security risk management, the usage of existing security risk management techniques, and security risk standards should be integrated with business process phases to protect against security issues in cloud services. Full article
(This article belongs to the Special Issue Feature Paper in Computers)
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Article
Reinforcing SLA Consensus on Blockchain
Computers 2021, 10(12), 159; https://doi.org/10.3390/computers10120159 - 26 Nov 2021
Cited by 1 | Viewed by 994
Abstract
Cloud Infrastructure as a Service (IaaS) Service Level Agreements (SLAs) assessment constitutes the de facto area of interest and applications in the public cloud infrastructure. However, the domination of colossal corporations tends to monopolize the way metrics and Key Performance Indicators (KPIs) are [...] Read more.
Cloud Infrastructure as a Service (IaaS) Service Level Agreements (SLAs) assessment constitutes the de facto area of interest and applications in the public cloud infrastructure. However, the domination of colossal corporations tends to monopolize the way metrics and Key Performance Indicators (KPIs) are measured and determined, leading to governed environments where the clientele is unable to obtain accurate and unbiased assessment of SLAs. Leaning toward SLA self-assessment, this paper provides a fair SLA consensus approach with innate transparency and privacy by leveraging permissioned blockchains that are equipped with Trusted Execution Environments (TEEs). The SLA assessment intelligence is performed inside enclaved smart contracts isolated from the on-chain entities views. The result constitutes a permissioned blockchain ecosystem where the IaaS and their clientele commonly agree on all the respective SLA monitoring and computation rules beforehand, as defined in any SLA assessment process, while the SLA consensus scheme constantly audits the SLA metrics based on these pre-approved regulations. Full article
(This article belongs to the Special Issue Edge and Cloud Computing in IoT)
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Article
The Application of Deep Learning Algorithms for PPG Signal Processing and Classification
Computers 2021, 10(12), 158; https://doi.org/10.3390/computers10120158 - 25 Nov 2021
Cited by 2 | Viewed by 1144
Abstract
Photoplethysmography (PPG) is widely used in wearable devices due to its conveniency and cost-effective nature. From this signal, several biomarkers can be collected, such as heart and respiration rate. For the usual acquisition scenarios, PPG is an artefact-ridden signal, which mandates the need [...] Read more.
Photoplethysmography (PPG) is widely used in wearable devices due to its conveniency and cost-effective nature. From this signal, several biomarkers can be collected, such as heart and respiration rate. For the usual acquisition scenarios, PPG is an artefact-ridden signal, which mandates the need for the designated classification algorithms to be able to reduce the noise component effect on the classification. Within the selected classification algorithm, the hyperparameters’ adjustment is of utmost importance. This study aimed to develop a deep learning model for robust PPG wave detection, which includes finding each beat’s temporal limits, from which the peak can be determined. A study database consisting of 1100 records was created from experimental PPG measurements performed in 47 participants. Different deep learning models were implemented to classify the PPG: Long Short-Term Memory (LSTM), Bidirectional LSTM, and Convolutional Neural Network (CNN). The Bidirectional LSTM and the CNN-LSTM were investigated, using the PPG Synchrosqueezed Fourier Transform (SSFT) as the models’ input. Accuracy, precision, recall, and F1-score were evaluated for all models. The CNN-LSTM algorithm, with an SSFT input, was the best performing model with accuracy, precision, and recall of 0.894, 0.923, and 0.914, respectively. This model has shown to be competent in PPG detection and delineation tasks, under noise-corrupted signals, which justifies the use of this innovative approach. Full article
(This article belongs to the Special Issue Computing, Electrical and Industrial Systems 2021)
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Article
Machine Learning Approaches to Traffic Accident Analysis and Hotspot Prediction
Computers 2021, 10(12), 157; https://doi.org/10.3390/computers10120157 - 24 Nov 2021
Cited by 6 | Viewed by 1555
Abstract
Traffic accidents are one of the most important concerns of the world, since they result in numerous casualties, injuries, and fatalities each year, as well as significant economic losses. There are many factors that are responsible for causing road accidents. If these factors [...] Read more.
Traffic accidents are one of the most important concerns of the world, since they result in numerous casualties, injuries, and fatalities each year, as well as significant economic losses. There are many factors that are responsible for causing road accidents. If these factors can be better understood and predicted, it might be possible to take measures to mitigate the damages and its severity. The purpose of this work is to identify these factors using accident data from 2016 to 2019 from the district of Setúbal, Portugal. This work aims at developing models that can select a set of influential factors that may be used to classify the severity of an accident, supporting an analysis on the accident data. In addition, this study also proposes a predictive model for future road accidents based on past data. Various machine learning approaches are used to create these models. Supervised machine learning methods such as decision trees (DT), random forests (RF), logistic regression (LR), and naive Bayes (NB) are used, as well as unsupervised machine learning techniques including DBSCAN and hierarchical clustering. Results show that a rule-based model using the C5.0 algorithm is capable of accurately detecting the most relevant factors describing a road accident severity. Further, the results of the predictive model suggests the RF model could be a useful tool for forecasting accident hotspots. Full article
(This article belongs to the Special Issue Machine Learning for Traffic Modeling and Prediction)
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Article
Smart Master Production Schedule for the Supply Chain: A Conceptual Framework
Computers 2021, 10(12), 156; https://doi.org/10.3390/computers10120156 - 23 Nov 2021
Cited by 3 | Viewed by 1674
Abstract
Risks arising from the effect of disruptions and unsustainable practices constantly push the supply chain to uncompetitive positions. A smart production planning and control process must successfully address both risks by reducing them, thereby strengthening supply chain (SC) resilience and its ability to [...] Read more.
Risks arising from the effect of disruptions and unsustainable practices constantly push the supply chain to uncompetitive positions. A smart production planning and control process must successfully address both risks by reducing them, thereby strengthening supply chain (SC) resilience and its ability to survive in the long term. On the one hand, the antidisruptive potential and the inherent sustainability implications of the zero-defect manufacturing (ZDM) management model should be highlighted. On the other hand, the digitization and virtualization of processes by Industry 4.0 (I4.0) digital technologies, namely digital twin (DT) technology, enable new simulation and optimization methods, especially in combination with machine learning (ML) procedures. This paper reviews the state of the art and proposes a ZDM strategy-based conceptual framework that models, optimizes and simulates the master production schedule (MPS) problem to maximize service levels in SCs. This conceptual framework will serve as a starting point for developing new MPS optimization models and algorithms in supply chain 4.0 (SC4.0) environments. Full article
(This article belongs to the Special Issue Computing, Electrical and Industrial Systems 2021)
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