Artificial intelligence(AI)plays a critical role in signal recognition of distributed sensor systems(DSS),boosting its applications in multiple monitoring fields.Due to the domain differences between massive sensors i...Artificial intelligence(AI)plays a critical role in signal recognition of distributed sensor systems(DSS),boosting its applications in multiple monitoring fields.Due to the domain differences between massive sensors in signal acquisition conditions,such as manufacturing process,deployment,and environments,current AI schemes for signal recognition of DSS frequently encounter poor generalization performance.In this paper,an adaptive decentralized artificial intelligence(ADAI)method for signal recognition of DSS is proposed,to improve the entire generalization performance.By fine-tuning pre-trained model with the unlabeled data in each domain,the ADAI scheme can train a series of adaptive AI models for all target domains,significantly reducing the false alarm rate(FAR)and missing alarm rate(MAR)induced by domain differences.The field tests about intrusion signal recognition with distributed optical fiber sensors system demonstrate the efficacy of the ADAI scheme,showcasing a FAR of merely 4.3%and 0%,along with a MAR of only 1.4%and 2.7%within two specific target domains.The ADAI scheme is expected to offer a practical paradigm for signal recognition of DSS in multiple application fields.展开更多
In order to increase the multiplexing density of the fiber Bragg gratings （FBGs） for a low cost per-sensor, based on the analysis of the spectrum shadow distortion （SSD）, a novel successive demultiplexing scheme f...In order to increase the multiplexing density of the fiber Bragg gratings （FBGs） for a low cost per-sensor, based on the analysis of the spectrum shadow distortion （SSD）, a novel successive demultiplexing scheme for FBG sensors has been developed. It is based on the optical cade division multiple access （CDMA） balanced demodulation. A high-density multiplexing-demultiplexing system for FBG sensors has been designed, and corresponding simulation carried out has demonstrated that the FBG sensors＇ reflective signals can still be obtained accurately and respectively, even if FBG sensors＇ operating bandwidths heavily overlap. The SSD has been greatly mitigated.展开更多
In an Underwater Wireless Sensor Network(UWSN),extreme energy loss is carried out by the early expiration of sensor nodes and causes a reduction in efficiency in the submerged acoustic sensor system.Systems based on c...In an Underwater Wireless Sensor Network(UWSN),extreme energy loss is carried out by the early expiration of sensor nodes and causes a reduction in efficiency in the submerged acoustic sensor system.Systems based on clustering strategies,instead of each node sending information by itself,utilize cluster heads to collect information inside the clusters for forwarding collective information to sink.This can effectively minimize the total energy loss during transmission.The environment of UWSN is 3D architecture-based and follows a complex hierarchical clustering strategy involving its most effecting unique parameters such as propagation delay and limited transmission bandwidth.Round base clustering strategy works in rounds,where each round comprises three fundamental stages:cluster head selection,grouping or node association,and data aggregation followed by forwarding data to the sink.In UWSN,the energy consumed during the formation of clusters has been considered casually or completely evaded in the previous works.In this paper,the cluster head setup period has been considered the main contributor to extra energy utilizer.A numerical channel model is proposed to compute extra energy.It is performed by using a UWSN broad model.The results have shown that extra maximum energy consumption is approximately 12.9 percent of the system total energy consumed in information transmissions.展开更多
Integration of sensors with engineering thermoplastics allows to track their health and surrounding stimuli.As one of vital backbones to construct sensor systems,copper(Cu)is highly conductive and cost-effective,yet t...Integration of sensors with engineering thermoplastics allows to track their health and surrounding stimuli.As one of vital backbones to construct sensor systems,copper(Cu)is highly conductive and cost-effective,yet tends to easily oxidize during and after processing.Herein,an in-situ integrated sensor system on engineering thermoplastics via hybrid laser direct writing is proposed,which primarily consists of laser-passivated functional Cu interconnects and laser-induced carbon-based sensors.Through a one-step photothermal treatment,the resulting functional Cu interconnects after reductive sintering and passivation are capable of resisting long-term oxidation failure at high temperatures(up to 170℃)without additional encapsulations.Interfacing with signal processing units,such an all-in-one system is applied for long-term and real-time temperature monitoring.This integrated sensor system with facile laser manufacturing strategies holds potentials for health monitoring and fault diagnosis of advanced equipment such as aircrafts,automobiles,high-speed trains,and medical devices.展开更多
This paper describes the analysis and design of an assistive device for elderly people under development at the EgyptJapan University of Science and Technology（E-JUST） named E-JUST assistive device（EJAD）.Several e...This paper describes the analysis and design of an assistive device for elderly people under development at the EgyptJapan University of Science and Technology（E-JUST） named E-JUST assistive device（EJAD）.Several experiments were carried out using a motion capture system（VICON） and inertial sensors to identify the human posture during the sit-to-stand motion.The EJAD uses only two inertial measurement units（IMUs） fused through an adaptive neuro-fuzzy inference systems（ANFIS） algorithm to imitate the real motion of the caregiver.The EJAD consists of two main parts,a robot arm and an active walker.The robot arm is a 2-degree-of-freedom（2-DOF） planar manipulator.In addition,a back support with a passive joint is used to support the patient s back.The IMUs on the leg and trunk of the patient are used to compensate for and adapt to the EJAD system motion depending on the obtained patient posture.The ANFIS algorithm is used to train the fuzzy system that converts the IMUs signals to the right posture of the patient.A control scheme is proposed to control the system motion based on practical measurements taken from the experiments.A computer simulation showed a relatively good performance of the EJAD in assisting the patient.展开更多
More than two decades ago, object-oriented representation of AEC （architecture engineering and construction） projects started to offer the promise of seamless communication of semantic data models between computer-b...More than two decades ago, object-oriented representation of AEC （architecture engineering and construction） projects started to offer the promise of seamless communication of semantic data models between computer-based systems used from the design stage to the operation of the facilities. BIM （building information modelling） emerged and appeared as a means to store all relevant data generated during the life-cycle of the facilities. But this upstream view of the built environment, arising from the design and construction stages, extended to the downstream operations where building and industrial facilities appeared more and more as huge dynamic data producers and concentrators while being operated. This created new challenges leading to what is referred to as ISCs （intelligent and smart constructions）. The current state of the art is that final constructions still contain various and increasingly versatile control and service systems, which are hardly standardised, and not interconnected among themselves. Monitoring, maintenance and services are done by specialised companies, each responsible of different systems, which are relying on customised software and techniques to meet specific user needs and are based on monolithic applications that require manual configuration for specific uses, maintenance and support. We demonstrate in this paper that the early promises of integration across the actors and along the life-time of facilities have gone a long way but will only be delivered through enhanced standardisation of computerized models, representations, services and operations still not yet fully accomplished 25 years after work started.展开更多
Recently, the subject on ＂plasmonics＂ has received significant attention in designing surface plasmon resonance （SPR） sensors. In order to achieve extremely high-sensitivity sensing, multilayered configurations ba...Recently, the subject on ＂plasmonics＂ has received significant attention in designing surface plasmon resonance （SPR） sensors. In order to achieve extremely high-sensitivity sensing, multilayered configurations based on a variety of active materials and dielectrics have been exploited. In this work, a novel SPR sensor is proposed and investigated theoretically. The structure, analyzed in attenuated total reflection （ATR）, consists of multilayer interfaces between gold and a metamaterial （LHM） separated by an analyte layer as a sensing medium. By interchanging between gold and LHM, under the effect of the refractive index （RI） of analyte set to be in the range of 1.00 to 1.99, the sharp peak reflectivity at the SPR angle takes two opposite behaviors predicted from the transfer matrix method. At the threshold value of 1.568 of the refractive index of analyte and when the LHM is the outer medium, the layered structure exhibits a giant sharp peak located at 43° of intensity up to 105 due to the Goos-Hanchen effect. With respect to the refractive index （RI） change and thickness of analyte, the characteristics （intensity, resonance condition, and quality factor） of the SPR mode, which make the proposed device have the potential for biosensing applications, have been analytically modelized.展开更多
The mission of Plant Phenomics is to publish novel research that will advance all aspects of plant phenotyping from the cell to the plant population levels using innovative combinations of sensor systems and data anal...The mission of Plant Phenomics is to publish novel research that will advance all aspects of plant phenotyping from the cell to the plant population levels using innovative combinations of sensor systems and data analytics.Plant Phenomics aims also to connect phenomics to other science domains,such as genomics,genetics,physiology,molecular biology,bioinformatics,statistics,mathematics,and computer sciences.The journal should thus contribute to advance plant sciences and agriculture/forestry/horticulture by addressing key scientific challenges in the area of plant phenomics.展开更多
The aim of maintenance is to reduce the number of failures in equipment and to avoid breakdowns that may lead to disruptions during operations.The objective of this study is to initiate the development of a predictive...The aim of maintenance is to reduce the number of failures in equipment and to avoid breakdowns that may lead to disruptions during operations.The objective of this study is to initiate the development of a predictive maintenance solution in the shipping industry based on a computational artificial intelligence model using real-time monitoring data.The data analysed originates from the historical values from sensors measuring the vessel´s engines and compressors health and the software used to analyse these data was R.The results demonstrated key parameters held a stronger influence in the overall state of the components and proved in most cases strong correlations amongst sensor data from the same equipment.The results also showed a great potential to serve as inputs for developing a predictive model,yet further elements including failure modes identification,detection of potential failures and asset criticality are some of the issues required to define prior designing the algorithms and a solution based on artificial intelligence.A systematic approach using big data and machine learning as techniques to create predictive maintenance strategies is already creating disruption within the shipping industry,and maritime organizations need to consider how to implement these new technologies into their business operations and to improve the speed and accuracy in their maintenance decision making.展开更多
Agriculture is the basis of every economy worldwide.Crop production is one of the major factors affecting domestic market condition in any country.Agricultural production is also a major prerequisite of economic devel...Agriculture is the basis of every economy worldwide.Crop production is one of the major factors affecting domestic market condition in any country.Agricultural production is also a major prerequisite of economic development,be it any part of any country.It plays a crucial role as it even provides raw material,employment and food to different citizens.A lot of issues are responsible for estimated crop production varying in different parts of the world.Some of these include overutilization of chemical fertilizers,presence of chemicals in water supply,uneven distribution of rainfall,different soil fertility and others.Other than these issues one of the commonly faced challenges across the globe equally includes destruction of themajor part of production due to diseases.After providing effective resources to the fields,major section of the production is diminished by the presence of diseases in the plants grown.This leads to focus on effective ways of detection of disease in plants.Presence of various diseases in plant is a major concern among farmers.Plant diseases acts as a major threat to small scale farmers as they lead tomajor destruction in overall food supply.To provide effectivemeasures for detection and avoidance of the destruction requires an early identification of type of plant disease present.In recent timemajorwork is being done for the identification of plant disease presents in varied parts of theworld affection varied crops.Majorwork is being done in the domain of identification of causing factors of these diseases.Someof the diseases are marked by the presence of viruses while some are resultant of fungal infection.This becomes a major issuewhen the causing factor is not traceable before it has already spread to major production section.This paper brings a review on effective use of different imaging techniques and computer vision approaches for the identification and classification of plant diseases.Detection of Plant disease is initiated with image acquisition followed by pre-processingwhile using the process of segmentation.It is further accompanied by different techniques used for feature extraction alongwith classification.In this Paper we present the Current Trends and Challenges for detection of plant disease using computer vision and advance imaging technique.展开更多
基金financial supports from the National Natural Science Foundation of China(NSFC)(No.61922033&U22A20206)Zhejiang Provincial Market Supervision Bureau Young Eagle Plan project under Grant CY2022228.
文摘Artificial intelligence(AI)plays a critical role in signal recognition of distributed sensor systems(DSS),boosting its applications in multiple monitoring fields.Due to the domain differences between massive sensors in signal acquisition conditions,such as manufacturing process,deployment,and environments,current AI schemes for signal recognition of DSS frequently encounter poor generalization performance.In this paper,an adaptive decentralized artificial intelligence(ADAI)method for signal recognition of DSS is proposed,to improve the entire generalization performance.By fine-tuning pre-trained model with the unlabeled data in each domain,the ADAI scheme can train a series of adaptive AI models for all target domains,significantly reducing the false alarm rate(FAR)and missing alarm rate(MAR)induced by domain differences.The field tests about intrusion signal recognition with distributed optical fiber sensors system demonstrate the efficacy of the ADAI scheme,showcasing a FAR of merely 4.3%and 0%,along with a MAR of only 1.4%and 2.7%within two specific target domains.The ADAI scheme is expected to offer a practical paradigm for signal recognition of DSS in multiple application fields.
基金supported by the Harbin Science Research Foundation under Grant No.2003AFQXJ004
文摘In order to increase the multiplexing density of the fiber Bragg gratings （FBGs） for a low cost per-sensor, based on the analysis of the spectrum shadow distortion （SSD）, a novel successive demultiplexing scheme for FBG sensors has been developed. It is based on the optical cade division multiple access （CDMA） balanced demodulation. A high-density multiplexing-demultiplexing system for FBG sensors has been designed, and corresponding simulation carried out has demonstrated that the FBG sensors＇ reflective signals can still be obtained accurately and respectively, even if FBG sensors＇ operating bandwidths heavily overlap. The SSD has been greatly mitigated.
文摘In an Underwater Wireless Sensor Network(UWSN),extreme energy loss is carried out by the early expiration of sensor nodes and causes a reduction in efficiency in the submerged acoustic sensor system.Systems based on clustering strategies,instead of each node sending information by itself,utilize cluster heads to collect information inside the clusters for forwarding collective information to sink.This can effectively minimize the total energy loss during transmission.The environment of UWSN is 3D architecture-based and follows a complex hierarchical clustering strategy involving its most effecting unique parameters such as propagation delay and limited transmission bandwidth.Round base clustering strategy works in rounds,where each round comprises three fundamental stages:cluster head selection,grouping or node association,and data aggregation followed by forwarding data to the sink.In UWSN,the energy consumed during the formation of clusters has been considered casually or completely evaded in the previous works.In this paper,the cluster head setup period has been considered the main contributor to extra energy utilizer.A numerical channel model is proposed to compute extra energy.It is performed by using a UWSN broad model.The results have shown that extra maximum energy consumption is approximately 12.9 percent of the system total energy consumed in information transmissions.
基金STI 2030-Major Projects(2022ZD0208601)National Natural Science Foundation of China(52105593)+2 种基金Zhejiang Provincial Natural Science Foundation of China(LDQ24E050001)‘Pioneer’and‘Leading Goose’R&D Program of Zhejiang(2023C01051)Fundamental Research Funds for the Central Universities(226-2024-00085)。
文摘Integration of sensors with engineering thermoplastics allows to track their health and surrounding stimuli.As one of vital backbones to construct sensor systems,copper(Cu)is highly conductive and cost-effective,yet tends to easily oxidize during and after processing.Herein,an in-situ integrated sensor system on engineering thermoplastics via hybrid laser direct writing is proposed,which primarily consists of laser-passivated functional Cu interconnects and laser-induced carbon-based sensors.Through a one-step photothermal treatment,the resulting functional Cu interconnects after reductive sintering and passivation are capable of resisting long-term oxidation failure at high temperatures(up to 170℃)without additional encapsulations.Interfacing with signal processing units,such an all-in-one system is applied for long-term and real-time temperature monitoring.This integrated sensor system with facile laser manufacturing strategies holds potentials for health monitoring and fault diagnosis of advanced equipment such as aircrafts,automobiles,high-speed trains,and medical devices.
基金supported in part by a scholarship provided by the Mission DepartmentMinistry of Higher Education of the Government of Egypt
文摘This paper describes the analysis and design of an assistive device for elderly people under development at the EgyptJapan University of Science and Technology（E-JUST） named E-JUST assistive device（EJAD）.Several experiments were carried out using a motion capture system（VICON） and inertial sensors to identify the human posture during the sit-to-stand motion.The EJAD uses only two inertial measurement units（IMUs） fused through an adaptive neuro-fuzzy inference systems（ANFIS） algorithm to imitate the real motion of the caregiver.The EJAD consists of two main parts,a robot arm and an active walker.The robot arm is a 2-degree-of-freedom（2-DOF） planar manipulator.In addition,a back support with a passive joint is used to support the patient s back.The IMUs on the leg and trunk of the patient are used to compensate for and adapt to the EJAD system motion depending on the obtained patient posture.The ANFIS algorithm is used to train the fuzzy system that converts the IMUs signals to the right posture of the patient.A control scheme is proposed to control the system motion based on practical measurements taken from the experiments.A computer simulation showed a relatively good performance of the EJAD in assisting the patient.
文摘More than two decades ago, object-oriented representation of AEC （architecture engineering and construction） projects started to offer the promise of seamless communication of semantic data models between computer-based systems used from the design stage to the operation of the facilities. BIM （building information modelling） emerged and appeared as a means to store all relevant data generated during the life-cycle of the facilities. But this upstream view of the built environment, arising from the design and construction stages, extended to the downstream operations where building and industrial facilities appeared more and more as huge dynamic data producers and concentrators while being operated. This created new challenges leading to what is referred to as ISCs （intelligent and smart constructions）. The current state of the art is that final constructions still contain various and increasingly versatile control and service systems, which are hardly standardised, and not interconnected among themselves. Monitoring, maintenance and services are done by specialised companies, each responsible of different systems, which are relying on customised software and techniques to meet specific user needs and are based on monolithic applications that require manual configuration for specific uses, maintenance and support. We demonstrate in this paper that the early promises of integration across the actors and along the life-time of facilities have gone a long way but will only be delivered through enhanced standardisation of computerized models, representations, services and operations still not yet fully accomplished 25 years after work started.
文摘Recently, the subject on ＂plasmonics＂ has received significant attention in designing surface plasmon resonance （SPR） sensors. In order to achieve extremely high-sensitivity sensing, multilayered configurations based on a variety of active materials and dielectrics have been exploited. In this work, a novel SPR sensor is proposed and investigated theoretically. The structure, analyzed in attenuated total reflection （ATR）, consists of multilayer interfaces between gold and a metamaterial （LHM） separated by an analyte layer as a sensing medium. By interchanging between gold and LHM, under the effect of the refractive index （RI） of analyte set to be in the range of 1.00 to 1.99, the sharp peak reflectivity at the SPR angle takes two opposite behaviors predicted from the transfer matrix method. At the threshold value of 1.568 of the refractive index of analyte and when the LHM is the outer medium, the layered structure exhibits a giant sharp peak located at 43° of intensity up to 105 due to the Goos-Hanchen effect. With respect to the refractive index （RI） change and thickness of analyte, the characteristics （intensity, resonance condition, and quality factor） of the SPR mode, which make the proposed device have the potential for biosensing applications, have been analytically modelized.
文摘The mission of Plant Phenomics is to publish novel research that will advance all aspects of plant phenotyping from the cell to the plant population levels using innovative combinations of sensor systems and data analytics.Plant Phenomics aims also to connect phenomics to other science domains,such as genomics,genetics,physiology,molecular biology,bioinformatics,statistics,mathematics,and computer sciences.The journal should thus contribute to advance plant sciences and agriculture/forestry/horticulture by addressing key scientific challenges in the area of plant phenomics.
文摘The aim of maintenance is to reduce the number of failures in equipment and to avoid breakdowns that may lead to disruptions during operations.The objective of this study is to initiate the development of a predictive maintenance solution in the shipping industry based on a computational artificial intelligence model using real-time monitoring data.The data analysed originates from the historical values from sensors measuring the vessel´s engines and compressors health and the software used to analyse these data was R.The results demonstrated key parameters held a stronger influence in the overall state of the components and proved in most cases strong correlations amongst sensor data from the same equipment.The results also showed a great potential to serve as inputs for developing a predictive model,yet further elements including failure modes identification,detection of potential failures and asset criticality are some of the issues required to define prior designing the algorithms and a solution based on artificial intelligence.A systematic approach using big data and machine learning as techniques to create predictive maintenance strategies is already creating disruption within the shipping industry,and maritime organizations need to consider how to implement these new technologies into their business operations and to improve the speed and accuracy in their maintenance decision making.
文摘Agriculture is the basis of every economy worldwide.Crop production is one of the major factors affecting domestic market condition in any country.Agricultural production is also a major prerequisite of economic development,be it any part of any country.It plays a crucial role as it even provides raw material,employment and food to different citizens.A lot of issues are responsible for estimated crop production varying in different parts of the world.Some of these include overutilization of chemical fertilizers,presence of chemicals in water supply,uneven distribution of rainfall,different soil fertility and others.Other than these issues one of the commonly faced challenges across the globe equally includes destruction of themajor part of production due to diseases.After providing effective resources to the fields,major section of the production is diminished by the presence of diseases in the plants grown.This leads to focus on effective ways of detection of disease in plants.Presence of various diseases in plant is a major concern among farmers.Plant diseases acts as a major threat to small scale farmers as they lead tomajor destruction in overall food supply.To provide effectivemeasures for detection and avoidance of the destruction requires an early identification of type of plant disease present.In recent timemajorwork is being done for the identification of plant disease presents in varied parts of theworld affection varied crops.Majorwork is being done in the domain of identification of causing factors of these diseases.Someof the diseases are marked by the presence of viruses while some are resultant of fungal infection.This becomes a major issuewhen the causing factor is not traceable before it has already spread to major production section.This paper brings a review on effective use of different imaging techniques and computer vision approaches for the identification and classification of plant diseases.Detection of Plant disease is initiated with image acquisition followed by pre-processingwhile using the process of segmentation.It is further accompanied by different techniques used for feature extraction alongwith classification.In this Paper we present the Current Trends and Challenges for detection of plant disease using computer vision and advance imaging technique.
