2023
Mehannaoui R, Mouss K-N, AKSA K.
IoT-based food traceability system: Architecture, technologies, applications, and future trends. Food Control [Internet]. 2023;145.
Publisher's VersionAbstractAn effective Food Traceability System (FTS) in a Food Supply Chain (FSC) should adequately provide all necessary information to the consumer(s), meet the requirements of the relevant agencies, and improve food safety as well as consumer confidence. New information and communication technologies are rapidly advancing, especially after the emergence of the Internet of Things (IoT). Consequently, new food traceability systems have become mainly based on IoT. Many studies have been conducted on food traceability. They mainly focused on the practical implementation and theoretical concepts. Accordingly, various definitions, technologies, and principles have been proposed. The “traceability” concept has been defined in several ways and each new definition has tried to generalize its previous ones. Nevertheless, no standard definition has been reached. Furthermore, the architecture of IoT-based food traceability systems has not yet been standardized. Similarly, used technologies in this field have not been yet well classified. This article presents an analysis of the existing definitions of food traceability, and thus proposes a new one that aims to be simpler, general, and encompassing than the previous ones. We also propose, through this article, a new architecture for IoT-based food traceability systems as well as a new classification of technologies used in this context. We do not miss discussing the applications of different technologies and future trends in the field of IoT-based food traceability systems. Mainly, an FTS can make use of three types of technologies: Identification and Monitoring Technologies (IMT), Communication Technologies (CT), and Data Management Technologies (DMT). Improving a food traceability system requires the use of the best new technologies. There is a variety of promising technologies today to enhance FTS, such as fifth-generation (5G) mobile communication systems and distributed ledger technology (DLT).
Mehannaoui R, Mouss K-N, AKSA K.
IoT-based food traceability system: Architecture, technologies, applications, and future trends. Food Control [Internet]. 2023;145.
Publisher's VersionAbstractAn effective Food Traceability System (FTS) in a Food Supply Chain (FSC) should adequately provide all necessary information to the consumer(s), meet the requirements of the relevant agencies, and improve food safety as well as consumer confidence. New information and communication technologies are rapidly advancing, especially after the emergence of the Internet of Things (IoT). Consequently, new food traceability systems have become mainly based on IoT. Many studies have been conducted on food traceability. They mainly focused on the practical implementation and theoretical concepts. Accordingly, various definitions, technologies, and principles have been proposed. The “traceability” concept has been defined in several ways and each new definition has tried to generalize its previous ones. Nevertheless, no standard definition has been reached. Furthermore, the architecture of IoT-based food traceability systems has not yet been standardized. Similarly, used technologies in this field have not been yet well classified. This article presents an analysis of the existing definitions of food traceability, and thus proposes a new one that aims to be simpler, general, and encompassing than the previous ones. We also propose, through this article, a new architecture for IoT-based food traceability systems as well as a new classification of technologies used in this context. We do not miss discussing the applications of different technologies and future trends in the field of IoT-based food traceability systems. Mainly, an FTS can make use of three types of technologies: Identification and Monitoring Technologies (IMT), Communication Technologies (CT), and Data Management Technologies (DMT). Improving a food traceability system requires the use of the best new technologies. There is a variety of promising technologies today to enhance FTS, such as fifth-generation (5G) mobile communication systems and distributed ledger technology (DLT).
Mehannaoui R, Mouss K-N, AKSA K.
IoT-based food traceability system: Architecture, technologies, applications, and future trends. Food Control [Internet]. 2023;145.
Publisher's VersionAbstractAn effective Food Traceability System (FTS) in a Food Supply Chain (FSC) should adequately provide all necessary information to the consumer(s), meet the requirements of the relevant agencies, and improve food safety as well as consumer confidence. New information and communication technologies are rapidly advancing, especially after the emergence of the Internet of Things (IoT). Consequently, new food traceability systems have become mainly based on IoT. Many studies have been conducted on food traceability. They mainly focused on the practical implementation and theoretical concepts. Accordingly, various definitions, technologies, and principles have been proposed. The “traceability” concept has been defined in several ways and each new definition has tried to generalize its previous ones. Nevertheless, no standard definition has been reached. Furthermore, the architecture of IoT-based food traceability systems has not yet been standardized. Similarly, used technologies in this field have not been yet well classified. This article presents an analysis of the existing definitions of food traceability, and thus proposes a new one that aims to be simpler, general, and encompassing than the previous ones. We also propose, through this article, a new architecture for IoT-based food traceability systems as well as a new classification of technologies used in this context. We do not miss discussing the applications of different technologies and future trends in the field of IoT-based food traceability systems. Mainly, an FTS can make use of three types of technologies: Identification and Monitoring Technologies (IMT), Communication Technologies (CT), and Data Management Technologies (DMT). Improving a food traceability system requires the use of the best new technologies. There is a variety of promising technologies today to enhance FTS, such as fifth-generation (5G) mobile communication systems and distributed ledger technology (DLT).
Berghout T, Mouss M-D, Mouss L‐H, Benbouzid M.
ProgNet: A Transferable Deep Network for Aircraft Engine Damage Propagation Prognosis under Real Flight Conditions. Aerospace [Internet]. 2023;10 (1).
Publisher's VersionAbstractMachine learning prognosis for condition monitoring of safety-critical systems, such as aircraft engines, continually faces challenges of data unavailability, complexity, and drift. Consequently, this paper overcomes these challenges by introducing adaptive deep transfer learning methodologies, strengthened with robust feature engineering. Initially, data engineering encompassing: (i) principal component analysis (PCA) dimensionality reduction; (ii) feature selection using correlation analysis; (iii) denoising with empirical Bayesian Cauchy prior wavelets; and (iv) feature scaling is used to obtain the required learning representations. Next, an adaptive deep learning model, namely ProgNet, is trained on a source domain with sufficient degradation trajectories generated from PrognosEase, a run-to-fail data generator for health deterioration analysis. Then, ProgNet is transferred to the target domain of obtained degradation features for fine-tuning. The primary goal is to achieve a higher-level generalization while reducing algorithmic complexity, making experiments reproducible on available commercial computers with quad-core microprocessors. ProgNet is tested on the popular New Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) dataset describing real flight scenarios. To the extent we can report, this is the first time that all N-CMAPSS subsets have been fully screened in such an experiment. ProgNet evaluations with numerous metrics, including the well-known CMAPSS scoring function, demonstrate promising performance levels, reaching 234.61 for the entire test set. This is approximately four times better than the results obtained with the compared conventional deep learning models.
Berghout T, Mouss M-D, Mouss L‐H, Benbouzid M.
ProgNet: A Transferable Deep Network for Aircraft Engine Damage Propagation Prognosis under Real Flight Conditions. Aerospace [Internet]. 2023;10 (1).
Publisher's VersionAbstractMachine learning prognosis for condition monitoring of safety-critical systems, such as aircraft engines, continually faces challenges of data unavailability, complexity, and drift. Consequently, this paper overcomes these challenges by introducing adaptive deep transfer learning methodologies, strengthened with robust feature engineering. Initially, data engineering encompassing: (i) principal component analysis (PCA) dimensionality reduction; (ii) feature selection using correlation analysis; (iii) denoising with empirical Bayesian Cauchy prior wavelets; and (iv) feature scaling is used to obtain the required learning representations. Next, an adaptive deep learning model, namely ProgNet, is trained on a source domain with sufficient degradation trajectories generated from PrognosEase, a run-to-fail data generator for health deterioration analysis. Then, ProgNet is transferred to the target domain of obtained degradation features for fine-tuning. The primary goal is to achieve a higher-level generalization while reducing algorithmic complexity, making experiments reproducible on available commercial computers with quad-core microprocessors. ProgNet is tested on the popular New Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) dataset describing real flight scenarios. To the extent we can report, this is the first time that all N-CMAPSS subsets have been fully screened in such an experiment. ProgNet evaluations with numerous metrics, including the well-known CMAPSS scoring function, demonstrate promising performance levels, reaching 234.61 for the entire test set. This is approximately four times better than the results obtained with the compared conventional deep learning models.
Berghout T, Mouss M-D, Mouss L‐H, Benbouzid M.
ProgNet: A Transferable Deep Network for Aircraft Engine Damage Propagation Prognosis under Real Flight Conditions. Aerospace [Internet]. 2023;10 (1).
Publisher's VersionAbstractMachine learning prognosis for condition monitoring of safety-critical systems, such as aircraft engines, continually faces challenges of data unavailability, complexity, and drift. Consequently, this paper overcomes these challenges by introducing adaptive deep transfer learning methodologies, strengthened with robust feature engineering. Initially, data engineering encompassing: (i) principal component analysis (PCA) dimensionality reduction; (ii) feature selection using correlation analysis; (iii) denoising with empirical Bayesian Cauchy prior wavelets; and (iv) feature scaling is used to obtain the required learning representations. Next, an adaptive deep learning model, namely ProgNet, is trained on a source domain with sufficient degradation trajectories generated from PrognosEase, a run-to-fail data generator for health deterioration analysis. Then, ProgNet is transferred to the target domain of obtained degradation features for fine-tuning. The primary goal is to achieve a higher-level generalization while reducing algorithmic complexity, making experiments reproducible on available commercial computers with quad-core microprocessors. ProgNet is tested on the popular New Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) dataset describing real flight scenarios. To the extent we can report, this is the first time that all N-CMAPSS subsets have been fully screened in such an experiment. ProgNet evaluations with numerous metrics, including the well-known CMAPSS scoring function, demonstrate promising performance levels, reaching 234.61 for the entire test set. This is approximately four times better than the results obtained with the compared conventional deep learning models.
Berghout T, Mouss M-D, Mouss L‐H, Benbouzid M.
ProgNet: A Transferable Deep Network for Aircraft Engine Damage Propagation Prognosis under Real Flight Conditions. Aerospace [Internet]. 2023;10 (1).
Publisher's VersionAbstractMachine learning prognosis for condition monitoring of safety-critical systems, such as aircraft engines, continually faces challenges of data unavailability, complexity, and drift. Consequently, this paper overcomes these challenges by introducing adaptive deep transfer learning methodologies, strengthened with robust feature engineering. Initially, data engineering encompassing: (i) principal component analysis (PCA) dimensionality reduction; (ii) feature selection using correlation analysis; (iii) denoising with empirical Bayesian Cauchy prior wavelets; and (iv) feature scaling is used to obtain the required learning representations. Next, an adaptive deep learning model, namely ProgNet, is trained on a source domain with sufficient degradation trajectories generated from PrognosEase, a run-to-fail data generator for health deterioration analysis. Then, ProgNet is transferred to the target domain of obtained degradation features for fine-tuning. The primary goal is to achieve a higher-level generalization while reducing algorithmic complexity, making experiments reproducible on available commercial computers with quad-core microprocessors. ProgNet is tested on the popular New Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) dataset describing real flight scenarios. To the extent we can report, this is the first time that all N-CMAPSS subsets have been fully screened in such an experiment. ProgNet evaluations with numerous metrics, including the well-known CMAPSS scoring function, demonstrate promising performance levels, reaching 234.61 for the entire test set. This is approximately four times better than the results obtained with the compared conventional deep learning models.
Bouatia M, Demagh R, Derriche Z.
numerical investigation of buried pipelines subjected to permanent ground deformation due to shallow slope failure (part i: transverse behaviour). Jordan Journal of Civil Engineering, JJCE [Internet]. 2023;17 (1).
Publisher's VersionAbstractPermanent Ground Deformations (PGD) that follow slope failures caused catastrophic damages on buried pipelines. This paper presents a two-dimensional numerical analysis of the behavior of an 800mm water transport pipeline buried in the Aine-Tine slope (Mila, Algeria) subjected to shallow PGD triggered by the recent earthquake of August 07th, 2020 (M= 4.9). The soil-pipeline interaction was simulated focusing on the effect of (1) the magnitudes of the PGD and (2) the rigidity of the pipeline on the structural response of the pipeline. The pipeline deformations (i.e., translation and ovalization) and radial internal efforts (i.e., axial forces F_A, shear forces F_S, and bending moments M_B) result highlighted that shallow PGD can cause additional loads on pipelines that are proportional to the magnitude of PGD. Moreover, it was found that rigid pipelines are more performant than flexible pipelines. Through a simplified numerical simulation, the study helps engineers and planners to predict the actual causes of pipeline leaks and ruptures leading to severe disruption of their normal operations.
Bouatia M, Demagh R, Derriche Z.
numerical investigation of buried pipelines subjected to permanent ground deformation due to shallow slope failure (part i: transverse behaviour). Jordan Journal of Civil Engineering, JJCE [Internet]. 2023;17 (1).
Publisher's VersionAbstractPermanent Ground Deformations (PGD) that follow slope failures caused catastrophic damages on buried pipelines. This paper presents a two-dimensional numerical analysis of the behavior of an 800mm water transport pipeline buried in the Aine-Tine slope (Mila, Algeria) subjected to shallow PGD triggered by the recent earthquake of August 07th, 2020 (M= 4.9). The soil-pipeline interaction was simulated focusing on the effect of (1) the magnitudes of the PGD and (2) the rigidity of the pipeline on the structural response of the pipeline. The pipeline deformations (i.e., translation and ovalization) and radial internal efforts (i.e., axial forces F_A, shear forces F_S, and bending moments M_B) result highlighted that shallow PGD can cause additional loads on pipelines that are proportional to the magnitude of PGD. Moreover, it was found that rigid pipelines are more performant than flexible pipelines. Through a simplified numerical simulation, the study helps engineers and planners to predict the actual causes of pipeline leaks and ruptures leading to severe disruption of their normal operations.
Bouatia M, Demagh R, Derriche Z.
numerical investigation of buried pipelines subjected to permanent ground deformation due to shallow slope failure (part i: transverse behaviour). Jordan Journal of Civil Engineering, JJCE [Internet]. 2023;17 (1).
Publisher's VersionAbstractPermanent Ground Deformations (PGD) that follow slope failures caused catastrophic damages on buried pipelines. This paper presents a two-dimensional numerical analysis of the behavior of an 800mm water transport pipeline buried in the Aine-Tine slope (Mila, Algeria) subjected to shallow PGD triggered by the recent earthquake of August 07th, 2020 (M= 4.9). The soil-pipeline interaction was simulated focusing on the effect of (1) the magnitudes of the PGD and (2) the rigidity of the pipeline on the structural response of the pipeline. The pipeline deformations (i.e., translation and ovalization) and radial internal efforts (i.e., axial forces F_A, shear forces F_S, and bending moments M_B) result highlighted that shallow PGD can cause additional loads on pipelines that are proportional to the magnitude of PGD. Moreover, it was found that rigid pipelines are more performant than flexible pipelines. Through a simplified numerical simulation, the study helps engineers and planners to predict the actual causes of pipeline leaks and ruptures leading to severe disruption of their normal operations.
Hammadi A, Brinis N, Djidel M.
Hydrodynamic Characteristics of the “Complex Terminal” aquifer in the Region of Oued Righ North (Algerian Sahara). Algerian Journal of Environmental Science and Technology [Internet]. 2023.
Publisher's VersionAbstractAccessibility of fresh water, the nature’s gift wheels the foremost part of the world economy. The sufficient supplies of water are essential for agriculture, human intake, industry as well as regeneration. The Oued Righ region is located in Algeria’s South-East, specifically in the NorthEast of the Sahara, on the Northern edge of the Grand Erg Oriental and the Southern border of the Aures massif. This area appears as a lower Sahara synclinal basin and is part of a broad North-South trending ditch. It is famous for its date palms, the development of the date culture in this region is attributed not only to the population’s efforts, but above all to the particular climatic conditions, the favorable soil characteristics and the existence of significant groundwater. The aim of this study is to understand the results obtained from using different approaches of water hydrodynamics in the Complex Terminal aquifer. The aquifer’s hydrodynamic characterization was carried out using hydrodynamic parameters and piezometry. As a result, the transmissivity and permeability obtained data using traditional Cooper-Jacob method showed that the flow capacities of the aquifer environment and the productivities of the structures are important in the studied zone where, the highest value of transmissivity equal 2.36× 102-m 2 /sis found in the central part of the study area in El-Meghair. The establishment of piezometric maps reveals a flow direction oriented toward the chott.
Hammadi A, Brinis N, Djidel M.
Hydrodynamic Characteristics of the “Complex Terminal” aquifer in the Region of Oued Righ North (Algerian Sahara). Algerian Journal of Environmental Science and Technology [Internet]. 2023.
Publisher's VersionAbstractAccessibility of fresh water, the nature’s gift wheels the foremost part of the world economy. The sufficient supplies of water are essential for agriculture, human intake, industry as well as regeneration. The Oued Righ region is located in Algeria’s South-East, specifically in the NorthEast of the Sahara, on the Northern edge of the Grand Erg Oriental and the Southern border of the Aures massif. This area appears as a lower Sahara synclinal basin and is part of a broad North-South trending ditch. It is famous for its date palms, the development of the date culture in this region is attributed not only to the population’s efforts, but above all to the particular climatic conditions, the favorable soil characteristics and the existence of significant groundwater. The aim of this study is to understand the results obtained from using different approaches of water hydrodynamics in the Complex Terminal aquifer. The aquifer’s hydrodynamic characterization was carried out using hydrodynamic parameters and piezometry. As a result, the transmissivity and permeability obtained data using traditional Cooper-Jacob method showed that the flow capacities of the aquifer environment and the productivities of the structures are important in the studied zone where, the highest value of transmissivity equal 2.36× 102-m 2 /sis found in the central part of the study area in El-Meghair. The establishment of piezometric maps reveals a flow direction oriented toward the chott.
Hammadi A, Brinis N, Djidel M.
Hydrodynamic Characteristics of the “Complex Terminal” aquifer in the Region of Oued Righ North (Algerian Sahara). Algerian Journal of Environmental Science and Technology [Internet]. 2023.
Publisher's VersionAbstractAccessibility of fresh water, the nature’s gift wheels the foremost part of the world economy. The sufficient supplies of water are essential for agriculture, human intake, industry as well as regeneration. The Oued Righ region is located in Algeria’s South-East, specifically in the NorthEast of the Sahara, on the Northern edge of the Grand Erg Oriental and the Southern border of the Aures massif. This area appears as a lower Sahara synclinal basin and is part of a broad North-South trending ditch. It is famous for its date palms, the development of the date culture in this region is attributed not only to the population’s efforts, but above all to the particular climatic conditions, the favorable soil characteristics and the existence of significant groundwater. The aim of this study is to understand the results obtained from using different approaches of water hydrodynamics in the Complex Terminal aquifer. The aquifer’s hydrodynamic characterization was carried out using hydrodynamic parameters and piezometry. As a result, the transmissivity and permeability obtained data using traditional Cooper-Jacob method showed that the flow capacities of the aquifer environment and the productivities of the structures are important in the studied zone where, the highest value of transmissivity equal 2.36× 102-m 2 /sis found in the central part of the study area in El-Meghair. The establishment of piezometric maps reveals a flow direction oriented toward the chott.