Pub Date : 2022-01-04DOI: 10.3390/engproc2021012068
Sophia Nawaz Gishkori, Ghulam Abbas, A. Shah, S. Rahman, M. S. Haider, Fahid Nisar
In this study we report biofuel potential in waste cake obtained from oil refinery. The sample was analyzed for its calorific value using auto bomb calorimeter (LECO AC-500), proximate analysis using Thermogravimetric analyzer (LECO 701) and elemental analysis using CHNS analyzer (LECO Tru-Spec). The elemental analysis of dry waste cake vs wet cake depicted the percentage composition of carbon (49.8%, 40.8%), hydrogen (7.9%, 6.0%), nitrogen (2.8%, 1.9%), Sulphur (1.9%, 0.5%) and oxygen content (37.6%, 40.4%). As for as the thermal degradation behavior of dry and wet cake in TGA is concerned, higher moisture contents (68.50%) found in wet cake and lower in dry cake (40.1%). Whereas the volatile matter in dry cake (30.9%) and low volatile in wet cake (14.3%). Similarly, %age of ash become high in dry cake (17.3%) and low in wet cake (5.11%). The results reflected that higher heating value of dry waste cake is higher (22.5 MJ/kg) than wet waste cake (20.5 MJ/kg) and commonly used sugarcane bagasse (17.88 MJ/kg).
{"title":"Potential Bio-Fuel from Refinery Waste through Anaerobic Digestion","authors":"Sophia Nawaz Gishkori, Ghulam Abbas, A. Shah, S. Rahman, M. S. Haider, Fahid Nisar","doi":"10.3390/engproc2021012068","DOIUrl":"https://doi.org/10.3390/engproc2021012068","url":null,"abstract":"In this study we report biofuel potential in waste cake obtained from oil refinery. The sample was analyzed for its calorific value using auto bomb calorimeter (LECO AC-500), proximate analysis using Thermogravimetric analyzer (LECO 701) and elemental analysis using CHNS analyzer (LECO Tru-Spec). The elemental analysis of dry waste cake vs wet cake depicted the percentage composition of carbon (49.8%, 40.8%), hydrogen (7.9%, 6.0%), nitrogen (2.8%, 1.9%), Sulphur (1.9%, 0.5%) and oxygen content (37.6%, 40.4%). As for as the thermal degradation behavior of dry and wet cake in TGA is concerned, higher moisture contents (68.50%) found in wet cake and lower in dry cake (40.1%). Whereas the volatile matter in dry cake (30.9%) and low volatile in wet cake (14.3%). Similarly, %age of ash become high in dry cake (17.3%) and low in wet cake (5.11%). The results reflected that higher heating value of dry waste cake is higher (22.5 MJ/kg) than wet waste cake (20.5 MJ/kg) and commonly used sugarcane bagasse (17.88 MJ/kg).","PeriodicalId":11748,"journal":{"name":"Engineering Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90308276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-04DOI: 10.3390/engproc2021012065
Yasir Rafique, A. Hussain
The energy efficiency of a power plant is largely determined by the vibrations of bearings that hold the shaft rotating at high speed which need to be critically controlled. This study presents the relative vibration modeling of a shaft bearing that is installed in a 660 MW supercritical steam turbine system. The operational data in raw form after being cleaned using machine learning based visualization and extensive data processing helped in training and validation of SVM and ANN models which are then compared by external validation tests. The model with best results is then used for the simulations of constructed operating scenarios. The ANN has been further tested for the complete operational load range (353 MW to 662 MW) which predicted the reduction in relative vibrations. Moreover, the validated ANN model has been used to develop many strategies of vibration reduction which helped in achieving more than 4% reduction in relative vibrations. Subsequently, an operational strategy that predicts a significant reduction in the bearing vibration levels is selected. For confirmation of the accuracy of prediction by ANN process model, the selected strategy has been used with the actual power plant. This assures the significant reduction of bearing vibration less than the alarm limit.
{"title":"Energy Efficient Strategy Development of Steam Turbine through Vibration Reduction Using ANN and SVM Approaches","authors":"Yasir Rafique, A. Hussain","doi":"10.3390/engproc2021012065","DOIUrl":"https://doi.org/10.3390/engproc2021012065","url":null,"abstract":"The energy efficiency of a power plant is largely determined by the vibrations of bearings that hold the shaft rotating at high speed which need to be critically controlled. This study presents the relative vibration modeling of a shaft bearing that is installed in a 660 MW supercritical steam turbine system. The operational data in raw form after being cleaned using machine learning based visualization and extensive data processing helped in training and validation of SVM and ANN models which are then compared by external validation tests. The model with best results is then used for the simulations of constructed operating scenarios. The ANN has been further tested for the complete operational load range (353 MW to 662 MW) which predicted the reduction in relative vibrations. Moreover, the validated ANN model has been used to develop many strategies of vibration reduction which helped in achieving more than 4% reduction in relative vibrations. Subsequently, an operational strategy that predicts a significant reduction in the bearing vibration levels is selected. For confirmation of the accuracy of prediction by ANN process model, the selected strategy has been used with the actual power plant. This assures the significant reduction of bearing vibration less than the alarm limit.","PeriodicalId":11748,"journal":{"name":"Engineering Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78055574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-04DOI: 10.3390/engproc2021012069
Asad Muneer, Ahsan Fayyaz, Shabab Iqbal, M. W. Jabbar, Arslan Qaisar, Faisal Farooq
This paper introduces and uses a single-phase, high-power LED driver with a battery backup. The buck–boost converter and reverse converter are both combined to achieve optimal performance. In the first part of the integrated circuit, the buck–boost converter is simply used to adjust the power when operating in the non-continuous operating mode. The reverse converter provides free voltage to the LEDs when released as a remote DC–DC converter. The battery backup cycle directly charges the battery at the same power as the LED driver required and provides charging power when there is no electricity. This paper demonstrates the functionality of the entire system and proves that it is an effective solution for new lighting applications.
{"title":"Single Stage Active Power Factor Correction Circuit for Street LED Light with Battery Backup","authors":"Asad Muneer, Ahsan Fayyaz, Shabab Iqbal, M. W. Jabbar, Arslan Qaisar, Faisal Farooq","doi":"10.3390/engproc2021012069","DOIUrl":"https://doi.org/10.3390/engproc2021012069","url":null,"abstract":"This paper introduces and uses a single-phase, high-power LED driver with a battery backup. The buck–boost converter and reverse converter are both combined to achieve optimal performance. In the first part of the integrated circuit, the buck–boost converter is simply used to adjust the power when operating in the non-continuous operating mode. The reverse converter provides free voltage to the LEDs when released as a remote DC–DC converter. The battery backup cycle directly charges the battery at the same power as the LED driver required and provides charging power when there is no electricity. This paper demonstrates the functionality of the entire system and proves that it is an effective solution for new lighting applications.","PeriodicalId":11748,"journal":{"name":"Engineering Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87839510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-31DOI: 10.3390/engproc2021013009
S. Corrado, Tejas G. Puranik, D. Mavris
Global modernization efforts focus on increasing aviation system capacity and efficiency, while maintaining high levels of safety. To accomplish these objectives, new analysis methods are required that consider Air Traffic Management (ATM) system operations at both the flight level and the airspace level. With the expansion of ADS-B technology, open-source flight tracking data has become more readily available to enable larger-scale analyses of aircraft operations. Specifically, anomaly detection has been identified as being paramount. However, previous analyses of airspace-level operational states have not considered the observation of transitional (transitioning between two distinct airspace-level operational patterns) or anomalous operational states. Therefore, a method is proposed in which the time-series trajectory data of all aircraft operating within a terminal airspace during a specified time period is aggregated to generate a representation of the airspace-level operational states such that a recursive DBSCAN procedure to characterize airspace-level operational states as either nominal, transitional, or anomalous as well as to identify the distinct nominal operational patterns. This method is demonstrated on one year of ADS-B trajectory data for aircraft arriving at San Francisco International Airport (KSFO). Overall, visual inspection of results indicate the method’s promise in assisting ATM system operators, decision-makers, and planners in designing the implementation of new operational concepts.
{"title":"Characterizing Terminal Airspace Operational States and Detecting Airspace-Level Anomalies","authors":"S. Corrado, Tejas G. Puranik, D. Mavris","doi":"10.3390/engproc2021013009","DOIUrl":"https://doi.org/10.3390/engproc2021013009","url":null,"abstract":"Global modernization efforts focus on increasing aviation system capacity and efficiency, while maintaining high levels of safety. To accomplish these objectives, new analysis methods are required that consider Air Traffic Management (ATM) system operations at both the flight level and the airspace level. With the expansion of ADS-B technology, open-source flight tracking data has become more readily available to enable larger-scale analyses of aircraft operations. Specifically, anomaly detection has been identified as being paramount. However, previous analyses of airspace-level operational states have not considered the observation of transitional (transitioning between two distinct airspace-level operational patterns) or anomalous operational states. Therefore, a method is proposed in which the time-series trajectory data of all aircraft operating within a terminal airspace during a specified time period is aggregated to generate a representation of the airspace-level operational states such that a recursive DBSCAN procedure to characterize airspace-level operational states as either nominal, transitional, or anomalous as well as to identify the distinct nominal operational patterns. This method is demonstrated on one year of ADS-B trajectory data for aircraft arriving at San Francisco International Airport (KSFO). Overall, visual inspection of results indicate the method’s promise in assisting ATM system operators, decision-makers, and planners in designing the implementation of new operational concepts.","PeriodicalId":11748,"journal":{"name":"Engineering Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74624200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-31DOI: 10.3390/engproc2021012055
Talha Mukhtar, Sunil Jamil, Usman Arif, Waleed Razzaq, Muhammad Wasif
This paper presents an automatic system for sorting and grading lemons using computer vision. It eliminates human errors in sorting processes. Lemons are sorted into three categories; ripe, semi-ripe, and a combined class of defective and unripe. A camera is used to capture an image of the lemon, and image analysis is done using Raspberry Pi. A conveyor belt system and a mechanical pusher put the lemon into its respective class.
{"title":"Lemon Grading and Sorting Using Computer Vision","authors":"Talha Mukhtar, Sunil Jamil, Usman Arif, Waleed Razzaq, Muhammad Wasif","doi":"10.3390/engproc2021012055","DOIUrl":"https://doi.org/10.3390/engproc2021012055","url":null,"abstract":"This paper presents an automatic system for sorting and grading lemons using computer vision. It eliminates human errors in sorting processes. Lemons are sorted into three categories; ripe, semi-ripe, and a combined class of defective and unripe. A camera is used to capture an image of the lemon, and image analysis is done using Raspberry Pi. A conveyor belt system and a mechanical pusher put the lemon into its respective class.","PeriodicalId":11748,"journal":{"name":"Engineering Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78245628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-31DOI: 10.3390/engproc2021013008
M. Kocour, Karel Veselý, Igor Szöke, Santosh Kesiraju, Juan Zuluaga-Gómez, Alexander Blatt, Amrutha Prasad, Iuliia Nigmatulina, P. Motlícek, D. Klakow, Allan Tart, H. Atassi, Pavel, Kolčárek, Honza Černocký, Claudia Cevenini, K. Choukri, M. Rigault, Fabian Landis, Saeed, Sarfjoo, Chloe Salamin
This document describes our pipeline for automatic processing of ATCO pilot audio communication we developed as part of the ATCO2 project. So far, we collected two thousand hours of audio recordings that we either preprocessed for the transcribers or used for semi-supervised training. Both methods of using the collected data can further improve our pipeline by retraining our models. The proposed automatic processing pipeline is a cascade of many standalone components: (a) segmentation, (b) volume control, (c) signal-to-noise ratio filtering, (d) diarization, (e) ‘speech-to-text’ (ASR) module, (f) English language detection, (g) call-sign code recognition, (h) ATCO—pilot classification and (i) highlighting commands and values. The key component of the pipeline is a speech-to-text transcription system that has to be trained with real-world ATC data; otherwise, the performance is poor. In order to further improve speech-to-text performance, we apply both semi-supervised training with our recordings and the contextual adaptation that uses a list of plausible callsigns from surveillance data as auxiliary information. Downstream NLP/NLU tasks are important from an application point of view. These application tasks need accurate models operating on top of the real speech-to-text output; thus, there is a need for more data too. Creating ATC data is the main aspiration of the ATCO2 project. At the end of the project, the data will be packaged and distributed by ELDA.
{"title":"Automatic Processing Pipeline for Collecting and Annotating Air-Traffic Voice Communication Data","authors":"M. Kocour, Karel Veselý, Igor Szöke, Santosh Kesiraju, Juan Zuluaga-Gómez, Alexander Blatt, Amrutha Prasad, Iuliia Nigmatulina, P. Motlícek, D. Klakow, Allan Tart, H. Atassi, Pavel, Kolčárek, Honza Černocký, Claudia Cevenini, K. Choukri, M. Rigault, Fabian Landis, Saeed, Sarfjoo, Chloe Salamin","doi":"10.3390/engproc2021013008","DOIUrl":"https://doi.org/10.3390/engproc2021013008","url":null,"abstract":"This document describes our pipeline for automatic processing of ATCO pilot audio communication we developed as part of the ATCO2 project. So far, we collected two thousand hours of audio recordings that we either preprocessed for the transcribers or used for semi-supervised training. Both methods of using the collected data can further improve our pipeline by retraining our models. The proposed automatic processing pipeline is a cascade of many standalone components: (a) segmentation, (b) volume control, (c) signal-to-noise ratio filtering, (d) diarization, (e) ‘speech-to-text’ (ASR) module, (f) English language detection, (g) call-sign code recognition, (h) ATCO—pilot classification and (i) highlighting commands and values. The key component of the pipeline is a speech-to-text transcription system that has to be trained with real-world ATC data; otherwise, the performance is poor. In order to further improve speech-to-text performance, we apply both semi-supervised training with our recordings and the contextual adaptation that uses a list of plausible callsigns from surveillance data as auxiliary information. Downstream NLP/NLU tasks are important from an application point of view. These application tasks need accurate models operating on top of the real speech-to-text output; thus, there is a need for more data too. Creating ATC data is the main aspiration of the ATCO2 project. At the end of the project, the data will be packaged and distributed by ELDA.","PeriodicalId":11748,"journal":{"name":"Engineering Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85016034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-31DOI: 10.3390/engproc2021009040
Lampros Tasiopoulos, M. Stefouli, Yorghos Voutos, Phivos Mylonas, E. Charou
Climate change could exacerbate floods on agricultural plains by increasing the frequency of extreme and adverse meteorological events. Flood extent maps could be a valuable source of information for agricultural land decision makers, risk management and emergency planning. We propose a method that combines various types of data and processing techniques in order to achieve accurate flood extent maps. The application aims to find the percentage of agricultural land that is covered by the floods through an automatic map estimation methodology based on the freely available Sentinel-2 (S2) satellite images and machine learning techniques.
{"title":"Machine Learning Techniques in Agricultural Flood Assessment and Monitoring Using Earth Observation and Hydromorphological Analysis","authors":"Lampros Tasiopoulos, M. Stefouli, Yorghos Voutos, Phivos Mylonas, E. Charou","doi":"10.3390/engproc2021009040","DOIUrl":"https://doi.org/10.3390/engproc2021009040","url":null,"abstract":"Climate change could exacerbate floods on agricultural plains by increasing the frequency of extreme and adverse meteorological events. Flood extent maps could be a valuable source of information for agricultural land decision makers, risk management and emergency planning. We propose a method that combines various types of data and processing techniques in order to achieve accurate flood extent maps. The application aims to find the percentage of agricultural land that is covered by the floods through an automatic map estimation methodology based on the freely available Sentinel-2 (S2) satellite images and machine learning techniques.","PeriodicalId":11748,"journal":{"name":"Engineering Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76712322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-31DOI: 10.3390/engproc2021009039
R. Silva, M. C. Fava, A. Saraiva, E. Mendiondo, C. Cugnasca, A. Delbem
This work proposes a data-driven theoretical framework for addressing: (i) extreme climate events prediction through multi-hazard risk mapping using remote sensing, artificial intelligence, and hydrological models, considering multiple hazards; and (ii) environmental monitoring using on-site data collection and IoT technologies. The framework considers the possibility of evaluating multiple climate change scenarios for improving decision-making in terms of Government policies and farm planning. Its main requirements are gathered based on a literature review. Several essential metrics that can be evaluated, considering both supervised and unsupervised metrics and key performance indicators considering the triple bottom line aspects, are also proposed. The framework also adopts multi-hazard (considering several hazards) and multi-risk (considering several relevant stakeholders) aspects and can be used to simulate different scenarios, an essential task for improving decision-making.
{"title":"A Theoretical Framework for Multi-Hazard Risk Mapping on Agricultural Areas Considering Artificial Intelligence, IoT, and Climate Change Scenarios","authors":"R. Silva, M. C. Fava, A. Saraiva, E. Mendiondo, C. Cugnasca, A. Delbem","doi":"10.3390/engproc2021009039","DOIUrl":"https://doi.org/10.3390/engproc2021009039","url":null,"abstract":"This work proposes a data-driven theoretical framework for addressing: (i) extreme climate events prediction through multi-hazard risk mapping using remote sensing, artificial intelligence, and hydrological models, considering multiple hazards; and (ii) environmental monitoring using on-site data collection and IoT technologies. The framework considers the possibility of evaluating multiple climate change scenarios for improving decision-making in terms of Government policies and farm planning. Its main requirements are gathered based on a literature review. Several essential metrics that can be evaluated, considering both supervised and unsupervised metrics and key performance indicators considering the triple bottom line aspects, are also proposed. The framework also adopts multi-hazard (considering several hazards) and multi-risk (considering several relevant stakeholders) aspects and can be used to simulate different scenarios, an essential task for improving decision-making.","PeriodicalId":11748,"journal":{"name":"Engineering Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81541490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-31DOI: 10.3390/engproc2021013010
J. Hoole, J. Booker, Jonathan Cooper
Significant challenges exist when defining the usage spectra of helicopter components due to the wide range of missions and manoeuvres flown by helicopters in-service. Automatic Dependent Surveillance-Broadcast (ADS-B) trajectories provide a means of constructing helicopter flight manoeuvre statistics across entire in-service fleets. This paper explores the feasibility of characterising helicopter manoeuvres by applying rule-based algorithms to ADS-B trajectories from a fleet of twin-seat training helicopters. Despite challenges relating to low-altitude ADS-B coverage, a comprehensive set of flight manoeuvre statistics was generated, which highlighted that significant variability exists in helicopter flight manoeuvre occurrences. The generated statistics can also support validation activities concerning design usage spectra assumptions.
{"title":"Helicopter Flight Manoeuvre Statistics via ADS-B: An Initial Investigation Using the OpenSky Network","authors":"J. Hoole, J. Booker, Jonathan Cooper","doi":"10.3390/engproc2021013010","DOIUrl":"https://doi.org/10.3390/engproc2021013010","url":null,"abstract":"Significant challenges exist when defining the usage spectra of helicopter components due to the wide range of missions and manoeuvres flown by helicopters in-service. Automatic Dependent Surveillance-Broadcast (ADS-B) trajectories provide a means of constructing helicopter flight manoeuvre statistics across entire in-service fleets. This paper explores the feasibility of characterising helicopter manoeuvres by applying rule-based algorithms to ADS-B trajectories from a fleet of twin-seat training helicopters. Despite challenges relating to low-altitude ADS-B coverage, a comprehensive set of flight manoeuvre statistics was generated, which highlighted that significant variability exists in helicopter flight manoeuvre occurrences. The generated statistics can also support validation activities concerning design usage spectra assumptions.","PeriodicalId":11748,"journal":{"name":"Engineering Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91313346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-31DOI: 10.3390/engproc2021009038
E. Lallas, A. Karageorgos, G. Ntalos
Illegal logging has always been considered as a major environmental and social global concern, as it is directly associated with deforestation and climate change. Nowadays, EU Regulation No 995/2010 has been successfully enforced to impede the placement of illegally produced timber within the EU market and therefore to efficiently enhance sustainable forest management and restore ecosystem balance. However, EU 995 regulatory compliance and enforcement itself is quite complex, since it requires long-term conformity, on a common basis for various heterogeneous groups and communities of stakeholders, in a global, even beyond EU, rule regulation framework. To make things worse, such a framework must be applied to the entire supply distribution chain and a wide variety of wood products, ranging from paper pulp to solid wood and flooring. Hence, in such complex and multivariate information environments, an ontological approach can more efficiently support regulatory compliance and knowledge management, due to its openness and richness of semantics for representing, analyzing, interpreting and managing such kind of information. In this paper, a rule-based regulatory compliance ontology is proposed, which fully captures EU Regulation No 995/2010 concepts and compliance rules and guidelines, as well as Greek legislations governing wood trade. The proposed ontology can be the basis for a computerized system providing automated support for illegal wood trade and monitoring EU regulation information provision and audit information storage and analysis.
{"title":"An Ontology Based Approach for Regulatory Compliance of EU Reg. No 995/2010 in Greece","authors":"E. Lallas, A. Karageorgos, G. Ntalos","doi":"10.3390/engproc2021009038","DOIUrl":"https://doi.org/10.3390/engproc2021009038","url":null,"abstract":"Illegal logging has always been considered as a major environmental and social global concern, as it is directly associated with deforestation and climate change. Nowadays, EU Regulation No 995/2010 has been successfully enforced to impede the placement of illegally produced timber within the EU market and therefore to efficiently enhance sustainable forest management and restore ecosystem balance. However, EU 995 regulatory compliance and enforcement itself is quite complex, since it requires long-term conformity, on a common basis for various heterogeneous groups and communities of stakeholders, in a global, even beyond EU, rule regulation framework. To make things worse, such a framework must be applied to the entire supply distribution chain and a wide variety of wood products, ranging from paper pulp to solid wood and flooring. Hence, in such complex and multivariate information environments, an ontological approach can more efficiently support regulatory compliance and knowledge management, due to its openness and richness of semantics for representing, analyzing, interpreting and managing such kind of information. In this paper, a rule-based regulatory compliance ontology is proposed, which fully captures EU Regulation No 995/2010 concepts and compliance rules and guidelines, as well as Greek legislations governing wood trade. The proposed ontology can be the basis for a computerized system providing automated support for illegal wood trade and monitoring EU regulation information provision and audit information storage and analysis.","PeriodicalId":11748,"journal":{"name":"Engineering Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79389937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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