Twelve low-calorie orange-based formulated jams were prepared mainly from orange, pumpkin and papaya, and then sweetened using fructose (F), stevioside (St) and sucralose (Su). The nutritional value of formulated jams...Twelve low-calorie orange-based formulated jams were prepared mainly from orange, pumpkin and papaya, and then sweetened using fructose (F), stevioside (St) and sucralose (Su). The nutritional value of formulated jams was estimated after the approximate chemical composition and total soluble solid have been determined. The effect of storage on total phenolic compounds, antioxidant capacity, carotenoids content and vitamin C was investigated. Organoleptical attributes of prepared low-calorie jams were done as well. Results indicated that the nutritive value [kcal 100 g–1 fw] ranged from 88.10 ± 0.60 to 164.34 ± 0.41;total phenol content (TPC, mg GAE 100 g–1 fw] ranged from 188.52 ± 2.45 to 411.79 ± 3.3;the antioxidant capacity (μmol TE g–1 fw) ranged from 14.57 ± 0.86 to 32.39 ± 1.19;total carotenoids [mg 100 g–1 fw] ranged from 115.20 ± 5.66 to 204.33 ± 4.21;vitamin C [mg 100 g fw] ranged from 8.94 ± 1.07 to 28.77 ± 4.46;total soluble solids [Brix] ranged from 22.53 ± 0.05 to 43.37 ± 0.13. Jams storage for a period of 12 months at room temperature led to a decrease in vitamin C content, TPC, antioxidant capacity, while total soluble solids (TSS) and carotenoids increased during storage. The results of organoleptical attributes showed that the formulas O11, O1 had the highest score of color and odor respectively while O7 recorded maximum score for taste, texture and bitterness respectively. Statistical analysis showed that storage intervals and treatments had a significant (p < 0.05) effect on sensory quality of diet jam. The organoleptical characteristics were affected with the extension of shelf-life. Addition of stevioside and sucralose to formulate the low-calorie jam increased total phenol and antioxidant capacity, improved color, taste and produced targeted low-calorie jams. The use of sweeteners such as fructose, sucralose and stevioside in the manufacture of orange diet jam was shown to be satisfactory, resulting in low-calorie jams, improved the quality and could be produced commercially.展开更多
Mainlobe jamming(MLJ)brings a big challenge for radar target detection,tracking,and identification.The suppression of MLJ is a hard task and an open problem in the electronic counter-counter measures(ECCM)field.Target...Mainlobe jamming(MLJ)brings a big challenge for radar target detection,tracking,and identification.The suppression of MLJ is a hard task and an open problem in the electronic counter-counter measures(ECCM)field.Target parameters and target direction estimation is difficult in radar MLJ.A target parameter estimation method via atom-reconstruction in radar MLJ is proposed in this paper.The proposed method can suppress the MLJ and simultaneously provide high estimation accuracy of target range and angle.Precisely,the eigen-projection matrix processing(EMP)algorithm is adopted to suppress the MLJ,and the target range is estimated effectively through the beamforming and pulse compression.Then the target angle can be effectively estimated by the atom-reconstruction method.Without any prior knowledge,the MLJ can be canceled,and the angle estimation accuracy is well preserved.Furthermore,the proposed method does not have strict requirement for radar array construction,and it can be applied for linear array and planar array.Moreover,the proposed method can effectively estimate the target azimuth and elevation simultaneously when the target azimuth(or elevation)equals to the jamming azimuth(or elevation),because the MLJ is suppressed in spatial plane dimension.展开更多
This paper investigates the jammerassisted multi-channel covert wireless communication(CWC)by exploiting the randomness of sub-channel selection to confuse the warden.In particular,we propose two sub-channel selection...This paper investigates the jammerassisted multi-channel covert wireless communication(CWC)by exploiting the randomness of sub-channel selection to confuse the warden.In particular,we propose two sub-channel selection transmission schemes,named random sub-channel selection(RSS)scheme and maximum sub-channel selection(MSS)scheme,to enhance communication covertness.For each proposed scheme,we first derive closed-form expressions of the transmission outage probability(TOP),the average effective rate,and the minimum average detection error probability(DEP).Then,the average effective covert rate(ECR)is maximized by jointly optimizing the transmit power at the transmitter and the number of sub-channels.Numerical results show that there is an optimal value of the number of sub-channels that maximizes the average ECR.We also find that to achieve the maximum average ECR,a larger number of subchannels are needed facing a stricter covertness constraint.展开更多
Passive jamming is believed to have very good potential in countermeasure community.In this paper,a passive angular blinking jamming method based on electronically controlled corner reflectors is proposed.The amplitud...Passive jamming is believed to have very good potential in countermeasure community.In this paper,a passive angular blinking jamming method based on electronically controlled corner reflectors is proposed.The amplitude of the incident wave can be modulated by switching the corner reflector between the penetration state and the reflection state,and the ensemble of multiple corner reflectors with towing rope can result in complex angle decoying effects.Dependency of the decoying effect on corner reflectors’radar cross section and positions are analyzed and simulated.Results show that the angle measured by a monopulse radar can be significantly interfered by this method while the automatic tracking is employed.展开更多
Offboard active decoys(OADs)can effectively jam monopulse radars.However,for missiles approaching from a particular direction and distance,the OAD should be placed at a specific location,posing high requirements for t...Offboard active decoys(OADs)can effectively jam monopulse radars.However,for missiles approaching from a particular direction and distance,the OAD should be placed at a specific location,posing high requirements for timing and deployment.To improve the response speed and jamming effect,a cluster of OADs based on an unmanned surface vehicle(USV)is proposed.The formation of the cluster determines the effectiveness of jamming.First,based on the mechanism of OAD jamming,critical conditions are identified,and a method for assessing the jamming effect is proposed.Then,for the optimization of the cluster formation,a mathematical model is built,and a multi-tribe adaptive particle swarm optimization algorithm based on mutation strategy and Metropolis criterion(3M-APSO)is designed.Finally,the formation optimization problem is solved and analyzed using the 3M-APSO algorithm under specific scenarios.The results show that the improved algorithm has a faster convergence rate and superior performance as compared to the standard Adaptive-PSO algorithm.Compared with a single OAD,the optimal formation of USV-OAD cluster effectively fills the blind area and maximizes the use of jamming resources.展开更多
In modern war,radar countermeasure is becoming increasingly fierce,and the enemy jamming time and pattern are changing more randomly.It is challenging for the radar to efficiently identify jamming and obtain precise p...In modern war,radar countermeasure is becoming increasingly fierce,and the enemy jamming time and pattern are changing more randomly.It is challenging for the radar to efficiently identify jamming and obtain precise parameter information,particularly in low signal-to-noise ratio(SNR)situations.In this paper,an approach to intelligent recognition and complex jamming parameter estimate based on joint time-frequency distribution features is proposed to address this challenging issue.Firstly,a joint algorithm based on YOLOv5 convolutional neural networks(CNNs)is proposed,which is used to achieve the jamming signal classification and preliminary parameter estimation.Furthermore,an accurate jamming key parameters estimation algorithm is constructed by comprehensively utilizing chi-square statistical test,feature region search,position regression,spectrum interpolation,etc.,which realizes the accurate estimation of jamming carrier frequency,relative delay,Doppler frequency shift,and other parameters.Finally,the approach has improved performance for complex jamming recognition and parameter estimation under low SNR,and the recognition rate can reach 98%under−15 dB SNR,according to simulation and real data verification results.展开更多
This study aims to identify the causes of sensor jams and its impact on the operation of vending machines. The vending machine is a machine that automatically dispenses products such as drinks, tickets, sandwiches and...This study aims to identify the causes of sensor jams and its impact on the operation of vending machines. The vending machine is a machine that automatically dispenses products such as drinks, tickets, sandwiches and biscuits, by inserting change or credit card into the machine. This technological feat is due to the advent of sensors. A sensor is a part of the measurement chain, it receives the quantity to be measured and provides information directly linked to this quantity. However, these vending robots are faced with malfunctions linked to sensor jams. The identification of the jam phenomenon was possible thanks to the inspection and monitoring of the various sensors installed on the vending robot. And Cadence software was used to model, control and locate the jammed sensor(s). The various tests were carried out by setting the robot in motion to better understand the causes of the phenomenon. The jam is therefore the phenomenon which triggers the sensors permanently, which causes the automatic vending robot to stop functioning. And this jam was due to the presence of water droplets on the sensor or dirt. This presence of water droplets on the sensor is linked to an increase in temperature. Controlling the temperature and locating the jammed sensor has made it possible to considerably reduce jamming and its harmful effects on the vending machine robot.展开更多
The study is aiming at preparation of low-calorie fruit nectars for diabetes and weight maintaining approaches as well as consumer satisfaction. Therefore, twenty low-calorie fruit-based formulated nectars were prepar...The study is aiming at preparation of low-calorie fruit nectars for diabetes and weight maintaining approaches as well as consumer satisfaction. Therefore, twenty low-calorie fruit-based formulated nectars were prepared mainly from orange, pomegranate, guava and mango pulps which sweetened with sucrose or sucrose— replaced at 25%, 50%, 75% and 100% using stevioside. Primitively, the yield of fresh fruits had been calculated. Consequently, nutritional, chemical and organoleptical characteristics of prepared fruit nectars have been determined. Results indicated that total solids content was in range of 5.57% - 13.20%, 9.90% - 14.37%, 8.25% - 13.27% and 8.25% - 16.50% for orange, pomegranate, guava and mango nectars, respectively. Dependently, caloric value resulted 21.57 to 51.08, 38.31 to 55.62, 31.93 to 51.37 and 31.93 to 63.86 kcal 100 g-1 fw for orange, pomegranate, guava and mango nectars, respectively. Total phenols content [TPC, mg GAE 100 g-1 dw] ranged from 665.12 to 747.41, 1180.42 to 1319.47, 742.54 to 848.27 and 418.01 to 472.42 for orange, pomegranate, guava and mango nectars, respectively. The antioxidant capacity by DPPH method [μmol TE g-1 dw] ranged from (20.79 to 26.51), (47.13 to 56.56), (60.68 to 69.25) and (8.39 to 13.32) for orange, pomegranate, guava and mango nectars, respectively. Total carotenoids [mg 100 g-1 dw] were the highest in mango nectars ranged from (102.99 to 110.52) in mango nectar with 100% sugar and mango nectar with 100% stevioside, respectively. Anthocyanins content recorded 6.14 mg 100 g-1 dw in pomegranate nectar with 100% sugar, while increased to be 9.01 mg 00 g-1 dw in pomegranate nectar with 100% stevioside. Ascorbic acid [mg 100 g fw] ranged from 23.41 to 27.53, 15.73 to 18.32, 25.72 to 30.87 and 18.07 to 20.98 for orange, pomegranate, guava and mango nectars, respectively. The results of organoleptical attributes showed no effect of sugar substituting by stevioside on color, odor and mouth feel. The most dramatic effect of sugar substituting had been observed on taste, bitter after taste and the overall acceptability of prepared nectars with high substitution levels. Practically, using stevioside to produce low-calorie nectars was shown to be satisfactory up to 50% - 75% substituting level, resulting low-calorie nectars and could be applied commercially.展开更多
To improve the recognition ability of communication jamming signals,Siamese Neural Network-based Open World Recognition(SNNOWR)is proposed.The algorithm can recognize known jamming classes,detect new(unknown)jamming c...To improve the recognition ability of communication jamming signals,Siamese Neural Network-based Open World Recognition(SNNOWR)is proposed.The algorithm can recognize known jamming classes,detect new(unknown)jamming classes,and unsupervised cluseter new classes.The network of SNN-OWR is trained supervised with paired input data consisting of two samples from a known dataset.On the one hand,the network is required to have the ability to distinguish whether two samples are from the same class.On the other hand,the latent distribution of known class is forced to approach their own unique Gaussian distribution,which is prepared for the subsequent open set testing.During the test,the unknown class detection process based on Gaussian probability density function threshold is designed,and an unsupervised clustering algorithm of the unknown jamming is realized by using the prior knowledge of known classes.The simulation results show that when the jamming-to-noise ratio is more than 0d B,the accuracy of SNN-OWR algorithm for known jamming classes recognition,unknown jamming detection and unsupervised clustering of unknown jamming is about 95%.This indicates that the SNN-OWR algorithm can make the effect of the recognition of unknown jamming be almost the same as that of known jamming.展开更多
The ultra-dense low earth orbit(LEO)integrated satellite-terrestrial networks(UDLEO-ISTN)can bring lots of benefits in terms of wide coverage,high capacity,and strong robustness.Meanwhile,the broadcasting and open nat...The ultra-dense low earth orbit(LEO)integrated satellite-terrestrial networks(UDLEO-ISTN)can bring lots of benefits in terms of wide coverage,high capacity,and strong robustness.Meanwhile,the broadcasting and open natures of satellite links also reveal many challenges for transmission security protection,especially for eavesdropping defence.How to efficiently take advantage of the LEO satellite’s density and ensure the secure communication by leveraging physical layer security with the cooperation of jammers deserves further investigation.To our knowledge,using satellites as jammers in UDLEO-ISTN is still a new problem since existing works mainly focused on this issue only from the aspect of terrestrial networks.To this end,we study in this paper the cooperative secrecy communication problem in UDLEOISTN by utilizing several satellites to send jamming signal to the eavesdroppers.An iterative scheme is proposed as our solution to maximize the system secrecy energy efficiency(SEE)via jointly optimizing transmit power allocation and user association.Extensive experiment results verify that our designed optimization scheme can significantly enhance the system SEE and achieve the optimal power allocation and user association strategies.展开更多
This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks onWireless Sensor Networks(WSNs).Jamming is a type of Denial of Service(DoS)attack and intentional ...This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks onWireless Sensor Networks(WSNs).Jamming is a type of Denial of Service(DoS)attack and intentional interference where a malicious node transmits a high-power signal to increase noise on the receiver side to disrupt the communication channel and reduce performance significantly.To defend and prevent such attacks,the first step is to detect them.The current detection approaches use centralized techniques to detect jamming,where each node collects information and forwards it to the base station.As a result,overhead and communication costs increased.In this work,we present a jamming attack and classify nodes into different categories based on their location to the jammer by employing a single node observer.As a result,we introduced a machine learning model that uses distance ratios and power received as features to detect such attacks.Furthermore,we considered several types of jammers transmitting at different power levels to evaluate the proposed metrics using MATLAB.With a detection accuracy of 99.7%for the k-nearest neighbors(KNN)algorithm and average testing accuracy of 99.9%,the presented solution is capable of efficiently and accurately detecting jamming attacks in wireless sensor networks.展开更多
Maritime communications with sea surface reflections and sea wave occlusions are susceptible to jamming attacks due to the wide geographical area and intensive wireless communication services.Unmanned Aerial Vehicles(...Maritime communications with sea surface reflections and sea wave occlusions are susceptible to jamming attacks due to the wide geographical area and intensive wireless communication services.Unmanned Aerial Vehicles(UAVs)help relay messages to improve communication performance,but the relay policy that depends on the rapidly changing maritime environments is difficult to optimize.In this paper,a reinforcement learning-based UAV relay policy for maritime communications is proposed to resist jamming attacks.Based on previous transmission performance,the relay location,the received power of the transmitted signal and the received jamming power,this scheme optimizes the UAV trajectory and relay power to save the energy consumption and decrease the Bit-Error-Rate(BER)of the maritime signals.A deep reinforcement learning-based scheme is also proposed,which designs a deep neural network with dueling architecture to further improve the communication performance and computational complexity.The performance bounds regarding the signal to interference plus noise ratio,energy consumption and the communication utility are provided based on the Nash equilibrium of the game against jamming,and the computational complexity of the proposed schemes is analyzed.Simulation results show that the proposed schemes improve the energy efficiency and decrease the BER compared with the benchmark.展开更多
Serious ice accumulating,pile-up and ice jamming occur around the conductor array of offshore jacket platforms during the winter every year in Bohai Sea,which could cause grave threats to the stability of platform str...Serious ice accumulating,pile-up and ice jamming occur around the conductor array of offshore jacket platforms during the winter every year in Bohai Sea,which could cause grave threats to the stability of platform structure,the safety of people and equipment,and even severer calamity.Therefore,the process of ice accumulation and ice jamming in the jacket platform area needs more concern.This study focuses on ice accumulation and jamming behaviors in the jacket platform conductor area by using a coupled two-dimensional hydro-ice dynamics model.A series of cases are conducted with different flow conditions,such as flow velocity,drifting direction and oscillatory flow.Through the simulation,the ice pile-up process is described and changes in ice-jamming thickness,ice pile-up location and ice pile-up volume are investigated.The differences in ice pile-up in the steady flow and oscillatory flow are analyzed.This study proposes a new approach to simulate the ice jamming process in the jacket platform conductor area,providing a reference for ice management on the platform.展开更多
The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking performance.Effective resource management can greatly ensure the combat capability of the NRS.In t...The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking performance.Effective resource management can greatly ensure the combat capability of the NRS.In this paper,based on the netted collocated multiple input multiple output(CMIMO)radar,an effective joint target assignment and power allocation(JTAPA)strategy for tracking multi-targets under self-defense blanket jamming is proposed.An architecture based on the distributed fusion is used in the radar network to estimate target state parameters.By deriving the predicted conditional Cramer-Rao lower bound(PC-CRLB)based on the obtained state estimation information,the objective function is formulated.To maximize the worst case tracking accuracy,the proposed JTAPA strategy implements an online target assignment and power allocation of all active nodes,subject to some resource constraints.Since the formulated JTAPA is non-convex,we propose an efficient two-step solution strategy.In terms of the simulation results,the proposed algorithm can effectively improve tracking performance in the worst case.展开更多
Traffic congestion is associated with increased environmental pollutions, as well as reduced socio-economic productivity due to significant delays in travel times. The consequences are worse in least developed countri...Traffic congestion is associated with increased environmental pollutions, as well as reduced socio-economic productivity due to significant delays in travel times. The consequences are worse in least developed countries where motorized road transport networks are often inefficiently managed in addition to being largely underdeveloped. Recent research on traffic congestion has mostly focused on infrastructural aspects of road networks, with little or no emphasis at all on motorists’ on-the-road behavior (MB). The current study thus aimed to bridge this knowledge gap by characterizing traffic jam incidents (TJI) observed over a period of 80 days in Uganda’s Capital City, Kampala. MB as well as road network infrastructural factors such as road blockage (RB), were captured for each of the observed TJI. A total of 483 peak-time TJI were recorded, and exploratory data analysis (EDA) subsequently performed on the TJI dataset. EDA involved Hierarchical clustering analysis (HCA) and K-means clustering of the TJI dataset, as well as a detailed descriptive statistical analysis of both the entire dataset and the emerging TJI clusters. A highlight finding of this study is that 48.2% of the observed TJIs were as a result of on-the-road motorist behavior. Furthermore, the intervention of traffic police officers in a bid to regulate traffic flow was equally responsible for 25.9% of the TJIs observed in this study. Overall, these results indicate that whereas road infrastructural improvement is warranted in order to improve traffic flow, introducing interventions to address inappropriate on-the-road motorists’ behavior could alone improve traffic flow in Kampala, by over 48%. Additionally, in-order to effectively regulate traffic flow in Kampala and other least developed cities with similar traffic congestion management practices, motorists’ on-the-road behavior ought to be factored into any data-driven mechanisms deployed to regulate traffic flow and thus potentially significantly curbing traffic congestion.展开更多
Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still fac...Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.展开更多
文摘Twelve low-calorie orange-based formulated jams were prepared mainly from orange, pumpkin and papaya, and then sweetened using fructose (F), stevioside (St) and sucralose (Su). The nutritional value of formulated jams was estimated after the approximate chemical composition and total soluble solid have been determined. The effect of storage on total phenolic compounds, antioxidant capacity, carotenoids content and vitamin C was investigated. Organoleptical attributes of prepared low-calorie jams were done as well. Results indicated that the nutritive value [kcal 100 g–1 fw] ranged from 88.10 ± 0.60 to 164.34 ± 0.41;total phenol content (TPC, mg GAE 100 g–1 fw] ranged from 188.52 ± 2.45 to 411.79 ± 3.3;the antioxidant capacity (μmol TE g–1 fw) ranged from 14.57 ± 0.86 to 32.39 ± 1.19;total carotenoids [mg 100 g–1 fw] ranged from 115.20 ± 5.66 to 204.33 ± 4.21;vitamin C [mg 100 g fw] ranged from 8.94 ± 1.07 to 28.77 ± 4.46;total soluble solids [Brix] ranged from 22.53 ± 0.05 to 43.37 ± 0.13. Jams storage for a period of 12 months at room temperature led to a decrease in vitamin C content, TPC, antioxidant capacity, while total soluble solids (TSS) and carotenoids increased during storage. The results of organoleptical attributes showed that the formulas O11, O1 had the highest score of color and odor respectively while O7 recorded maximum score for taste, texture and bitterness respectively. Statistical analysis showed that storage intervals and treatments had a significant (p < 0.05) effect on sensory quality of diet jam. The organoleptical characteristics were affected with the extension of shelf-life. Addition of stevioside and sucralose to formulate the low-calorie jam increased total phenol and antioxidant capacity, improved color, taste and produced targeted low-calorie jams. The use of sweeteners such as fructose, sucralose and stevioside in the manufacture of orange diet jam was shown to be satisfactory, resulting in low-calorie jams, improved the quality and could be produced commercially.
基金supported by the National Natural Science Foundation of China(6207148262001510)the Civil Aviation Administration o f China(U1733116)。
文摘Mainlobe jamming(MLJ)brings a big challenge for radar target detection,tracking,and identification.The suppression of MLJ is a hard task and an open problem in the electronic counter-counter measures(ECCM)field.Target parameters and target direction estimation is difficult in radar MLJ.A target parameter estimation method via atom-reconstruction in radar MLJ is proposed in this paper.The proposed method can suppress the MLJ and simultaneously provide high estimation accuracy of target range and angle.Precisely,the eigen-projection matrix processing(EMP)algorithm is adopted to suppress the MLJ,and the target range is estimated effectively through the beamforming and pulse compression.Then the target angle can be effectively estimated by the atom-reconstruction method.Without any prior knowledge,the MLJ can be canceled,and the angle estimation accuracy is well preserved.Furthermore,the proposed method does not have strict requirement for radar array construction,and it can be applied for linear array and planar array.Moreover,the proposed method can effectively estimate the target azimuth and elevation simultaneously when the target azimuth(or elevation)equals to the jamming azimuth(or elevation),because the MLJ is suppressed in spatial plane dimension.
文摘This paper investigates the jammerassisted multi-channel covert wireless communication(CWC)by exploiting the randomness of sub-channel selection to confuse the warden.In particular,we propose two sub-channel selection transmission schemes,named random sub-channel selection(RSS)scheme and maximum sub-channel selection(MSS)scheme,to enhance communication covertness.For each proposed scheme,we first derive closed-form expressions of the transmission outage probability(TOP),the average effective rate,and the minimum average detection error probability(DEP).Then,the average effective covert rate(ECR)is maximized by jointly optimizing the transmit power at the transmitter and the number of sub-channels.Numerical results show that there is an optimal value of the number of sub-channels that maximizes the average ECR.We also find that to achieve the maximum average ECR,a larger number of subchannels are needed facing a stricter covertness constraint.
基金supported by the Equipment Pre-research Project(GK202002A020068)。
文摘Passive jamming is believed to have very good potential in countermeasure community.In this paper,a passive angular blinking jamming method based on electronically controlled corner reflectors is proposed.The amplitude of the incident wave can be modulated by switching the corner reflector between the penetration state and the reflection state,and the ensemble of multiple corner reflectors with towing rope can result in complex angle decoying effects.Dependency of the decoying effect on corner reflectors’radar cross section and positions are analyzed and simulated.Results show that the angle measured by a monopulse radar can be significantly interfered by this method while the automatic tracking is employed.
基金the National Natural Science Foundation of China(Grant No.62101579).
文摘Offboard active decoys(OADs)can effectively jam monopulse radars.However,for missiles approaching from a particular direction and distance,the OAD should be placed at a specific location,posing high requirements for timing and deployment.To improve the response speed and jamming effect,a cluster of OADs based on an unmanned surface vehicle(USV)is proposed.The formation of the cluster determines the effectiveness of jamming.First,based on the mechanism of OAD jamming,critical conditions are identified,and a method for assessing the jamming effect is proposed.Then,for the optimization of the cluster formation,a mathematical model is built,and a multi-tribe adaptive particle swarm optimization algorithm based on mutation strategy and Metropolis criterion(3M-APSO)is designed.Finally,the formation optimization problem is solved and analyzed using the 3M-APSO algorithm under specific scenarios.The results show that the improved algorithm has a faster convergence rate and superior performance as compared to the standard Adaptive-PSO algorithm.Compared with a single OAD,the optimal formation of USV-OAD cluster effectively fills the blind area and maximizes the use of jamming resources.
基金supported by Shandong Provincial Natural Science Foundation(ZR2020MF015)Aerospace Technology Group Stability Support Project(ZY0110020009).
文摘In modern war,radar countermeasure is becoming increasingly fierce,and the enemy jamming time and pattern are changing more randomly.It is challenging for the radar to efficiently identify jamming and obtain precise parameter information,particularly in low signal-to-noise ratio(SNR)situations.In this paper,an approach to intelligent recognition and complex jamming parameter estimate based on joint time-frequency distribution features is proposed to address this challenging issue.Firstly,a joint algorithm based on YOLOv5 convolutional neural networks(CNNs)is proposed,which is used to achieve the jamming signal classification and preliminary parameter estimation.Furthermore,an accurate jamming key parameters estimation algorithm is constructed by comprehensively utilizing chi-square statistical test,feature region search,position regression,spectrum interpolation,etc.,which realizes the accurate estimation of jamming carrier frequency,relative delay,Doppler frequency shift,and other parameters.Finally,the approach has improved performance for complex jamming recognition and parameter estimation under low SNR,and the recognition rate can reach 98%under−15 dB SNR,according to simulation and real data verification results.
文摘This study aims to identify the causes of sensor jams and its impact on the operation of vending machines. The vending machine is a machine that automatically dispenses products such as drinks, tickets, sandwiches and biscuits, by inserting change or credit card into the machine. This technological feat is due to the advent of sensors. A sensor is a part of the measurement chain, it receives the quantity to be measured and provides information directly linked to this quantity. However, these vending robots are faced with malfunctions linked to sensor jams. The identification of the jam phenomenon was possible thanks to the inspection and monitoring of the various sensors installed on the vending robot. And Cadence software was used to model, control and locate the jammed sensor(s). The various tests were carried out by setting the robot in motion to better understand the causes of the phenomenon. The jam is therefore the phenomenon which triggers the sensors permanently, which causes the automatic vending robot to stop functioning. And this jam was due to the presence of water droplets on the sensor or dirt. This presence of water droplets on the sensor is linked to an increase in temperature. Controlling the temperature and locating the jammed sensor has made it possible to considerably reduce jamming and its harmful effects on the vending machine robot.
文摘The study is aiming at preparation of low-calorie fruit nectars for diabetes and weight maintaining approaches as well as consumer satisfaction. Therefore, twenty low-calorie fruit-based formulated nectars were prepared mainly from orange, pomegranate, guava and mango pulps which sweetened with sucrose or sucrose— replaced at 25%, 50%, 75% and 100% using stevioside. Primitively, the yield of fresh fruits had been calculated. Consequently, nutritional, chemical and organoleptical characteristics of prepared fruit nectars have been determined. Results indicated that total solids content was in range of 5.57% - 13.20%, 9.90% - 14.37%, 8.25% - 13.27% and 8.25% - 16.50% for orange, pomegranate, guava and mango nectars, respectively. Dependently, caloric value resulted 21.57 to 51.08, 38.31 to 55.62, 31.93 to 51.37 and 31.93 to 63.86 kcal 100 g-1 fw for orange, pomegranate, guava and mango nectars, respectively. Total phenols content [TPC, mg GAE 100 g-1 dw] ranged from 665.12 to 747.41, 1180.42 to 1319.47, 742.54 to 848.27 and 418.01 to 472.42 for orange, pomegranate, guava and mango nectars, respectively. The antioxidant capacity by DPPH method [μmol TE g-1 dw] ranged from (20.79 to 26.51), (47.13 to 56.56), (60.68 to 69.25) and (8.39 to 13.32) for orange, pomegranate, guava and mango nectars, respectively. Total carotenoids [mg 100 g-1 dw] were the highest in mango nectars ranged from (102.99 to 110.52) in mango nectar with 100% sugar and mango nectar with 100% stevioside, respectively. Anthocyanins content recorded 6.14 mg 100 g-1 dw in pomegranate nectar with 100% sugar, while increased to be 9.01 mg 00 g-1 dw in pomegranate nectar with 100% stevioside. Ascorbic acid [mg 100 g fw] ranged from 23.41 to 27.53, 15.73 to 18.32, 25.72 to 30.87 and 18.07 to 20.98 for orange, pomegranate, guava and mango nectars, respectively. The results of organoleptical attributes showed no effect of sugar substituting by stevioside on color, odor and mouth feel. The most dramatic effect of sugar substituting had been observed on taste, bitter after taste and the overall acceptability of prepared nectars with high substitution levels. Practically, using stevioside to produce low-calorie nectars was shown to be satisfactory up to 50% - 75% substituting level, resulting low-calorie nectars and could be applied commercially.
基金supported by the National Natural Science Foundation of China(U19B2016)Zhejiang Provincial Key Lab of Data Storage and Transmission Technology,Hangzhou Dianzi University。
文摘To improve the recognition ability of communication jamming signals,Siamese Neural Network-based Open World Recognition(SNNOWR)is proposed.The algorithm can recognize known jamming classes,detect new(unknown)jamming classes,and unsupervised cluseter new classes.The network of SNN-OWR is trained supervised with paired input data consisting of two samples from a known dataset.On the one hand,the network is required to have the ability to distinguish whether two samples are from the same class.On the other hand,the latent distribution of known class is forced to approach their own unique Gaussian distribution,which is prepared for the subsequent open set testing.During the test,the unknown class detection process based on Gaussian probability density function threshold is designed,and an unsupervised clustering algorithm of the unknown jamming is realized by using the prior knowledge of known classes.The simulation results show that when the jamming-to-noise ratio is more than 0d B,the accuracy of SNN-OWR algorithm for known jamming classes recognition,unknown jamming detection and unsupervised clustering of unknown jamming is about 95%.This indicates that the SNN-OWR algorithm can make the effect of the recognition of unknown jamming be almost the same as that of known jamming.
基金supported by National Key R&D Program of China(2022YFB3104200)in part by National Natural Science Foundation of China(62202386)+6 种基金in part by Basic Research Programs of Taicang(TC2021JC31)in part by Fundamental Research Funds for the Central Universities(D5000210817)in part by Xi’an Unmanned System Security and Intelligent Communications ISTC Centerin part by Special Funds for Central Universities Construction of World-Class Universities(Disciplines)and Special Development Guidance(0639022GH0202237 and 0639022SH0201237)in part by the Henan Key Scientific Research Program of Higher Education(23B510003,21A510008 and 21A510009)in part by Henan Key Scientific and Technological Projects(212102210553)。
文摘The ultra-dense low earth orbit(LEO)integrated satellite-terrestrial networks(UDLEO-ISTN)can bring lots of benefits in terms of wide coverage,high capacity,and strong robustness.Meanwhile,the broadcasting and open natures of satellite links also reveal many challenges for transmission security protection,especially for eavesdropping defence.How to efficiently take advantage of the LEO satellite’s density and ensure the secure communication by leveraging physical layer security with the cooperation of jammers deserves further investigation.To our knowledge,using satellites as jammers in UDLEO-ISTN is still a new problem since existing works mainly focused on this issue only from the aspect of terrestrial networks.To this end,we study in this paper the cooperative secrecy communication problem in UDLEOISTN by utilizing several satellites to send jamming signal to the eavesdroppers.An iterative scheme is proposed as our solution to maximize the system secrecy energy efficiency(SEE)via jointly optimizing transmit power allocation and user association.Extensive experiment results verify that our designed optimization scheme can significantly enhance the system SEE and achieve the optimal power allocation and user association strategies.
基金funded by the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia through the Project Number (IF-PSAU-2021/01/18707).
文摘This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks onWireless Sensor Networks(WSNs).Jamming is a type of Denial of Service(DoS)attack and intentional interference where a malicious node transmits a high-power signal to increase noise on the receiver side to disrupt the communication channel and reduce performance significantly.To defend and prevent such attacks,the first step is to detect them.The current detection approaches use centralized techniques to detect jamming,where each node collects information and forwards it to the base station.As a result,overhead and communication costs increased.In this work,we present a jamming attack and classify nodes into different categories based on their location to the jammer by employing a single node observer.As a result,we introduced a machine learning model that uses distance ratios and power received as features to detect such attacks.Furthermore,we considered several types of jammers transmitting at different power levels to evaluate the proposed metrics using MATLAB.With a detection accuracy of 99.7%for the k-nearest neighbors(KNN)algorithm and average testing accuracy of 99.9%,the presented solution is capable of efficiently and accurately detecting jamming attacks in wireless sensor networks.
基金This work was supported in part by the Funds of the National Natural Science Foundation of China under Grant(U21A20444,61971366)in part by the Fundamental Research Funds for the central universities No.20720210073.
文摘Maritime communications with sea surface reflections and sea wave occlusions are susceptible to jamming attacks due to the wide geographical area and intensive wireless communication services.Unmanned Aerial Vehicles(UAVs)help relay messages to improve communication performance,but the relay policy that depends on the rapidly changing maritime environments is difficult to optimize.In this paper,a reinforcement learning-based UAV relay policy for maritime communications is proposed to resist jamming attacks.Based on previous transmission performance,the relay location,the received power of the transmitted signal and the received jamming power,this scheme optimizes the UAV trajectory and relay power to save the energy consumption and decrease the Bit-Error-Rate(BER)of the maritime signals.A deep reinforcement learning-based scheme is also proposed,which designs a deep neural network with dueling architecture to further improve the communication performance and computational complexity.The performance bounds regarding the signal to interference plus noise ratio,energy consumption and the communication utility are provided based on the Nash equilibrium of the game against jamming,and the computational complexity of the proposed schemes is analyzed.Simulation results show that the proposed schemes improve the energy efficiency and decrease the BER compared with the benchmark.
基金jointly supported by the National Key R&D Program of China (Grant No.2021YFB2600700)the Central PublicInterest Scientific Institution Basal Research Fund of China (Grant Nos.Y221007 and Y223005)。
文摘Serious ice accumulating,pile-up and ice jamming occur around the conductor array of offshore jacket platforms during the winter every year in Bohai Sea,which could cause grave threats to the stability of platform structure,the safety of people and equipment,and even severer calamity.Therefore,the process of ice accumulation and ice jamming in the jacket platform area needs more concern.This study focuses on ice accumulation and jamming behaviors in the jacket platform conductor area by using a coupled two-dimensional hydro-ice dynamics model.A series of cases are conducted with different flow conditions,such as flow velocity,drifting direction and oscillatory flow.Through the simulation,the ice pile-up process is described and changes in ice-jamming thickness,ice pile-up location and ice pile-up volume are investigated.The differences in ice pile-up in the steady flow and oscillatory flow are analyzed.This study proposes a new approach to simulate the ice jamming process in the jacket platform conductor area,providing a reference for ice management on the platform.
基金National Natural Science Foundation of China(Grant No.62001506)to provide fund for conducting experiments。
文摘The netted radar system(NRS)has been proved to possess unique advantages in anti-jamming and improving target tracking performance.Effective resource management can greatly ensure the combat capability of the NRS.In this paper,based on the netted collocated multiple input multiple output(CMIMO)radar,an effective joint target assignment and power allocation(JTAPA)strategy for tracking multi-targets under self-defense blanket jamming is proposed.An architecture based on the distributed fusion is used in the radar network to estimate target state parameters.By deriving the predicted conditional Cramer-Rao lower bound(PC-CRLB)based on the obtained state estimation information,the objective function is formulated.To maximize the worst case tracking accuracy,the proposed JTAPA strategy implements an online target assignment and power allocation of all active nodes,subject to some resource constraints.Since the formulated JTAPA is non-convex,we propose an efficient two-step solution strategy.In terms of the simulation results,the proposed algorithm can effectively improve tracking performance in the worst case.
文摘Traffic congestion is associated with increased environmental pollutions, as well as reduced socio-economic productivity due to significant delays in travel times. The consequences are worse in least developed countries where motorized road transport networks are often inefficiently managed in addition to being largely underdeveloped. Recent research on traffic congestion has mostly focused on infrastructural aspects of road networks, with little or no emphasis at all on motorists’ on-the-road behavior (MB). The current study thus aimed to bridge this knowledge gap by characterizing traffic jam incidents (TJI) observed over a period of 80 days in Uganda’s Capital City, Kampala. MB as well as road network infrastructural factors such as road blockage (RB), were captured for each of the observed TJI. A total of 483 peak-time TJI were recorded, and exploratory data analysis (EDA) subsequently performed on the TJI dataset. EDA involved Hierarchical clustering analysis (HCA) and K-means clustering of the TJI dataset, as well as a detailed descriptive statistical analysis of both the entire dataset and the emerging TJI clusters. A highlight finding of this study is that 48.2% of the observed TJIs were as a result of on-the-road motorist behavior. Furthermore, the intervention of traffic police officers in a bid to regulate traffic flow was equally responsible for 25.9% of the TJIs observed in this study. Overall, these results indicate that whereas road infrastructural improvement is warranted in order to improve traffic flow, introducing interventions to address inappropriate on-the-road motorists’ behavior could alone improve traffic flow in Kampala, by over 48%. Additionally, in-order to effectively regulate traffic flow in Kampala and other least developed cities with similar traffic congestion management practices, motorists’ on-the-road behavior ought to be factored into any data-driven mechanisms deployed to regulate traffic flow and thus potentially significantly curbing traffic congestion.
基金the National Natural Science Foundation of China(No.62171462,No.62231027,No.U20B2038,No.61931011,No.62001514 and No.62271501).
文摘Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.Integrated sensing and communication(ISAC)is regarded as a recent advanced technology,which is expected to realize the dual functions of sensing and communication simultaneously in one system.Nevertheless,it still faces the challenges of the information security and transmission robustness caused by the openness of wireless channel,especially under antagonistic environment.Hence,this article develops a generalized framework,named cognitive joint jamming,sensing and communication(cognitive J2SAC),to empower the current sensing/communication/jamming system with a“brain”for realizing precise sensing,reliable communication and effective jamming under antagonistic environment.Three kinds of gains can be captured by cognitive J2SAC,including integrated gain,cooperative gain and cognitive gain.Moreover,we highlight the enabling mechanism among jamming,sensing,and communication,as well as illustrating several typical use cases of cognitive J2SAC.Furthermore,several key enabled technologies are analyzed and a typical sensing enhance integrated communication and jamming case study is discussed to verify the effectiveness of the proposed method.Last but not the least,the future directions are listed before concluding this article.