Study on Division Method of Quality Monitoring Control Area Based on Comprehensive Cultivated Land Attribute

The quality change of cultivated land resources requires the scientific deployment of monitoring areas.In this study,Yuzhou City is taken as an example to divide the quality monitoring control areas through the study of natural quality,utilization level,income level,and utilization characteristics,etc.Compared with the traditional administrative unit division or cultivated land quality division method,the regional homogeneity of this study is stronger,and there are quality differences between regions.It provides precondition and precision guarantee for the monitoring of cultivated land quality.

Impact of Village-based Health Education of Tobacco Control on the Current Smoking Rate in Chinese Rural Areas

The number of smokers in Chinese rural areas is more than 200 million, which is twice that in cities. It is very significant to carry out tobacco control interventions in rural areas. We performed this community intervention study to evaluate the efficacy of village-based health education of tobacco control on the male current smoking rate in rural areas. The population of this study was the males above 15 years old from 6 villages in rural areas. The villages were randomly assigned to intervention group or control group（3 villages in each group）. Self-designed smoking questionnaire was applied. The intervention group received the village-based health education of tobacco control for one year. The primary outcome measurement was the male current smoking rate. In the baseline investigation, completed surveys were returned by 814 male residents from the control group and 831 male residents from the intervention group. The male current smoking rate in the control group and the intervention group was 61.2% and 58.5%, respectively, before intervention. There was no significant difference between these two groups（P〉0.05）. After one-year intervention, the current smoking rate in the intervention group（51.2%） was significantly lower than that in the control group（62.8%）（P〈0.001）. Our study suggested that the village-based health education of tobacco control was effective in lowering the male current smoking rate in rural areas, which could be a suitable and feasible way for tobacco control in the Chinese rural areas.

A novel intrusion detection model for the CAN bus packet of in-vehicle network based on attention mechanism and autoencoder

The attacks on in-vehicle Controller Area Network(CAN)bus messages severely disrupt normal communication between vehicles.Therefore,researches on intrusion detection models for CAN have positive business value for vehicle security,and the intrusion detection technology for CAN bus messages can effectively protect the invehicle network from unlawful attacks.Previous machine learning-based models are unable to effectively identify intrusive abnormal messages due to their inherent shortcomings.Hence,to address the shortcomings of the previous machine learning-based intrusion detection technique,we propose a novel method using Attention Mechanism and AutoEncoder for Intrusion Detection(AMAEID).The AMAEID model first converts the raw hexadecimal message data into binary format to obtain better input.Then the AMAEID model encodes and decodes the binary message data using a multi-layer denoising autoencoder model to obtain a hidden feature representation that can represent the potential features behind the message data at a deeper level.Finally,the AMAEID model uses the attention mechanism and the fully connected layer network to infer whether the message is an abnormal message or not.The experimental results with three evaluation metrics on a real in-vehicle CAN bus message dataset outperform some traditional machine learning algorithms,demonstrating the effectiveness of the AMAEID model.

A Comprehensive Analysis of Datasets for Automotive Intrusion Detection Systems

Recently,automotive intrusion detection systems(IDSs)have emerged as promising defense approaches to counter attacks on in-vehicle networks(IVNs).However,the effectiveness of IDSs relies heavily on the quality of the datasets used for training and evaluation.Despite the availability of several datasets for automotive IDSs,there has been a lack of comprehensive analysis focusing on assessing these datasets.This paper aims to address the need for dataset assessment in the context of automotive IDSs.It proposes qualitative and quantitative metrics that are independent of specific automotive IDSs,to evaluate the quality of datasets.These metrics take into consideration various aspects such as dataset description,collection environment,and attack complexity.This paper evaluates eight commonly used datasets for automotive IDSs using the proposed metrics.The evaluation reveals biases in the datasets,particularly in terms of limited contexts and lack of diversity.Additionally,it highlights that the attacks in the datasets were mostly injected without considering normal behaviors,which poses challenges for training and evaluating machine learning-based IDSs.This paper emphasizes the importance of addressing the identified limitations in existing datasets to improve the performance and adaptability of automotive IDSs.The proposed metrics can serve as valuable guidelines for researchers and practitioners in selecting and constructing high-quality datasets for automotive security applications.Finally,this paper presents the requirements for high-quality datasets,including the need for representativeness,diversity,and balance.

FIDS:Filtering-Based Intrusion Detection System for In-Vehicle CAN

Modern vehicles are equipped with multiple Electronic Control Units(ECUs)that support various convenient driving functions,such as the Advanced Driver Assistance System(ADAS).To enable communication between these ECUs,the Controller Area Network(CAN)protocol is widely used.However,since CAN lacks any security technologies,it is vulnerable to cyber attacks.To address this,researchers have conducted studies on machine learning-based intrusion detection systems(IDSs)for CAN.However,most existing IDSs still have non-negligible detection errors.In this paper,we pro-pose a new filtering-based intrusion detection system(FIDS)to minimize the detection errors of machine learning-based IDSs.FIDS uses a whitelist and a blacklist created from CAN datasets.The whitelist stores the cryptographic hash value of normal packet sequences to correct false positives(FP),while the blacklist corrects false negatives(FN)based on transmission intervals and identifiers of CAN packets.We evaluated the performance of the proposed FIDS by implementing a machine learning-based IDS and applying FIDS to it.We conducted the evaluation using two CAN attack datasets provided by the Hacking and Countermeasure Research Lab(HCRL),which confirmed that FIDS can effectively reduce the FP and FN of the existing IDS.

Availability evaluation of controller area networks under the influence of intermittent connection faults

Controller area networks(CANs),as one of the widely used fieldbuses in the industry,have been extended to the automation field with strict standards for safety and reliability.In practice,factors such as fatigue and insulation wear of the cables can cause intermittent connection(IC)faults to occur frequently in the CAN,which will affect the dynamic behavior and the safety of the system.Hence,quantitatively evaluating the performance of the CAN under the influence of IC faults is crucial to real-time health monitoring of the system.In this paper,a novel methodology is proposed for real-time quantitative evaluation of CAN availability when considering IC faults,with the system availability parameter being calculated based on the network state transition model.First,the causal relationship between IC fault and network error response is constructed,based on which the IC fault arrival rate is estimated.Second,the states of the network considering IC faults are analyzed,and the deterministic and stochastic Petri net(DSPN)model is applied to describe the transition relationship of the states.Then,the parameters of the DSPN model are determined and the availability of the system is calculated based on the probability distribution and physical meaning of markings in the DSPN model.A testbed is constructed and case studies are conducted to verify the proposed methodology under various experimental setups.Experimental results show that the estimation results obtained using the proposed method agree well with the actual values.

MULTIPLE ELECTRONIC CONTROL UNITS CALIBRATION SYSTEM BASED ON EXPLICIT CALIBRATION PROTOCOL AND J1939 PROTOCOL

The rising number of electronic control units （ECUs） in vehicles and the decreasing time to market have led to the need for advanced methods of calibration. A multi-ECU calibration system was developed based on the explicit calibration protocol （XCP） and J1939 communication protocol to satisfy the need of calibrating multiple ECUs simultaneously. The messages in the controller area network （CAN） are defined in the J1939 protocol. Each CAN node can get its own calibration messages and information from other ECUs, and block other messages by qualifying the CAN messages with priority, source or destination address. The data field of the calibration message is designed with the XCP, with CAN acting as the transport layer. The calibration sessions are setup with the event-triggered XCP driver in the master node and the responding XCP driver in the slave nodes. Mirroring calibration variables from ROM to RAM enables the user to calibrate ECUs online. The application example shows that the multi-ECU calibration system can calibrate multiple ECUs simultaneously, and the main program can also accomplish its calculation and send commands to the actuators in time. By the multi-ECU calibration system, the calibration effort and time can be reduced and the variables in ECU can get a better match with the variables of other ECUs.

Development of a Robot for In-service Radiography Inspection of Subsea Flexible Risers

The extreme operational environmental conditions and aging conditions of subsea structures pose a risk to their structural integrity and is critical to their safety.Nondestructive testing is essential to identify defects developing within the structure,allowing repair in a timely manner to mitigate against failures that cause damage to the environment and pose a hazard to human operators.However,to be cost effective,inspections must be carried out without taking the risers out of service.This poses significant safety risks if undertaken manually.This paper presents the development of an automated inspection system for flexible risers that are used to connect wellheads on the seafloor to the offshore production and storage facility.Due to the complex structure of risers,radiography is considered as the best technique to inspect multiple layers of the risers.However,radiography inspection,in turn,requires a robotic system for in-situ inspection with higher payload capacity,precise movement of source and detector which is able to withstand an extreme operational environment.The deployment of a radiography inspection system hasbeen achieved bydeveloping acustomized subsearobotic system called RiserSure that can provide precise scanning motion of a gamma ray source and digital detector moving in alignment.The prototype has been tested on a flexible riser during shallow water sea trials with the system placed around a riser by a remotely operated vehicle.The results from the trials show that the internal inner and outer tensile armor layer and defects in the riser can be successfully imaged in real operational conditions.

An Approach for Damage Identification and Optimal Sensor Placement in Structural Health Monitoring by Genetic Algorithm Technique

Civil engineering structures are constructed for strength, serviceability and durability. The structures thus constructed involve huge investment and labour work. In order to protect the structure from various damages, periodic monitoring of structures is necessary. Hence Structural Health Monitoring (SHM) plays a vital role in diagnosing the state of the structure at every moment during its life period. For this purpose, sensors are deployed in the structures for its efficient health monitoring. Sensors cannot be deployed at random locations of the structure. They have to be located at those points which reflect the damage. In this study, a 3-storey and a 4-storey building are taken and Modal Strain Energy (MSE) is used for finding the initial locations of sensors. The number of sensors obtained is then optimized using Genetic Algorithm (GA) technique. Finally damages are induced in certain locations of the structure and a damage detection technique called as “Flexibility Matrix Based Technique (FMBT)” is introduced for damage localization in the structure.

Study on Intercepting Method for Nitrogen and Phosphorus in Ecological Ditches and Pond

[Objective] The research aimed to reduce emission load of the farmland runoff by using ecological ditches and pond. [Method] N and P intercepting project construction of the ecological ditches and pond in Zhaiji Village, Xiangcheng District, Suzhou City as research object, by repairing 1 834 m3 of original drainage ditches, newly excavating 6 800 m2 of ecological main ditches and 6 000 m2 of artificial purification ecological pond, etc., runoff emission load in real control area of the project was counted. [Result] Annual net loads of the runoff emission for TN and TP were respectively 2 552.22 and 95.00 kg in 33.3 hm2 of farmland. Annual runoff intercepting loads of TN and TP were respectively 1 225.07 and 50.35 kg in ditches. Annual runoff intercepting loads of TN and TP were respectively 1 327.15 and 44.65 kg in ecological pond. In effluent, TN concentration was 6.32 mg/L and was smaller than 15 mg/L. TP concentration was 0.25 mg/L and was smaller than 0.5 mg/L. They both reached level-one A discharge standard. [Conclusion] The research provided theoretical basis for effective control of the agricultural non-point source pollution in Taihu Lake basin.

Cascaded Multilevel Inverter Based Power and Signal Multiplex Transmission for Electric Vehicles

Power&signal multiplex transmission(P&SMT)is a technique that uses power electronic circuits for communication signal transmission.In this paper,a three-phase cascaded multilevel inverter-based P&S MT system is proposed.The proposed method can transmit communication signals without using a Controller Area Network bus,thereby reducing the wiring cost of the conventional electric vehicle(EV)communication system.The designed system can achieve motor speed regulation and battery balance discharging for EVs.With the combined pulse width modulation scheme and frequency shift keying method,both power and communication signals are transmitted successfully in a simulation model implemented in Matlab/Simulink.By evaluating the bit error rate of the transmitted signal,the maximum signal rate of the proposed system is determined as 600 bit/s.

A cooperative control strategy of resistance spot welding process by combining the constant current control with the DRC method

The modeling control method based on the dynamic resistance characteristics of good nuggets, that is the DRC method, is an improvement on the dynamic resistance threshold method for the quality control of resistance spot welding. But there is still a control blind area in the initial four cycles. For this reason, the quality of every weld nugget could not be fully ensured. Thus a new fuzzy cooperative control method is put forward. It uses a multi-information time-control mechanism by combining the constant current control technology with the DRC method in a relay way. This whole-process control strategy has led to a good control effect and produced the dual-identical results in the weld nugget quality and the welding time.

Data Driven CAN Node Reliability Assessment for Manufacturing System

The reliability of the Controller Area Network（CAN） is critical to the performance and safety of the system. However, direct bus-off time assessment tools are lacking in practice due to inaccessibility of the node information and the complexity of the node interactions upon errors. In order to measure the mean time to bus-off（MTTB） of all the nodes, a novel data driven node bus-off time assessment method for CAN network is proposed by directly using network error information. First, the corresponding network error event sequence for each node is constructed using multiple-layer network error information. Then, the generalized zero inflated Poisson process（GZIP） model is established for each node based on the error event sequence. Finally, the stochastic model is constructed to predict the MTTB of the node. The accelerated case studies with different error injection rates are conducted on a laboratory network to demonstrate the proposed method, where the network errors are generated by a computer controlled error injection system. Experiment results show that the MTTB of nodes predicted by the proposed method agree well with observations in the case studies. The proposed data driven node time to bus-off assessment method for CAN networks can successfully predict the MTTB of nodes by directly using network error event data.

Cloning and Analysis of the Promoter Region of Rat uPA Gene

Objective To clone and analyze the promoter sequence of rat urokinase plasminogen activator protein gene. Methods The genomic DNA was extracted from rat testicular tissue. According to urokinase plasminogen activator, the gene sense primer and antisense primer of uPA gene were designed and synthesized, then Touch-Down PCR were performed. After proper purification, the PCR product was sequenced, analyzed with the promoter prediction software and compared with the DNA sequence of rattuas urokinase plasminogen activator. Results The cloned uPA gene was about 1 572 bp in length, which contained a full open-reading frame with 21 bp in length exons, and the upper region of transcriptional start was 1 551 bp in length which was eucaryon transcriptional control area. The 5＇ UTR had a promoter region including a non-responsive TATA-box. Not only the GC-box binding region was found in this gene, but also active protein I （AP1） and SP1 were seen in other regions. Conclusion A 1 572 bp uPA gene fragment （GenBank accession No.X65651） was obtained from rat genomic DNA library, containing eucaryon transcriptional control area with a promoter region, non-conspicuous TATA-box, GC-box and an extron. A non-responsive TATA-box is located at the upper -30 region.

Integral Performance Criteria Based Analysis of Load Frequency Control in Bilateral Based Market

Performance index based analysis is made to examine and highlight the effective application of Particle Swarm Optimization (PSO) to optimize the Proportional Integral gains for Load Frequency Control (LFC) in a restructured power system that operates under Bilateral based policy scheme. Various Integral Performance Criteria measures are taken as fitness function in PSO and are compared using overshoot, settling time and frequency and tie-line power deviation following a step load perturbation (SLP). The motivation for using different fitness technique in PSO is to show the behavior of the controller for a wide range of system parameters and load changes. Error based analysis with parametric uncertainties and load changes are tested on a two-area restructured power system. The results of the proposed PSO based controller show the better performance compared to the classical Ziegler-Nichols (Z-N) tuned PI and Fuzzy Rule based PI controller.

A Delay-dependent Dynamic Wide Area Damping Controller for Renewable Energy Integrated Power System Resilient to Communication Failure

Integration of renewable energy sources(RES)with a conventional power system has a detrimental effect on interarea oscillation.Most popular RESs are solar photovoltaic(PV)and wind energy conversion systems(WECS).Both solar PV power generation and WECS are integrated with power systems using a power electronic converter.Increasing the amount of RES generation lead towards reduction of system damping,which leads towards inter-area oscillation.Also,the intermittent behavior of a RES reduces the effectiveness of damping controllers.A dynamic controller based wide area damping controller(WADC)is proposed in this paper to increase small signal stability of a RES integrated power system.The WADC is designed for contemplating delay in a communication channel,communication failure and saturation.An anti-windup compensator is developed to overcome the effect of actuator saturation.However,the gain of the anti-windup compensator is calculated using LyapunovKrasovskii functional(LKF)in terms of linear matrix inequality(LMI).The actuator considered in this paper is a unified power flow controller(UPFC).Efficacy of PV and wind power integration on power system is also observed.The efficacy of the developed dynamic controller is verified using IEEE 39 bus and 68 bus power system.

The Controlled Approach in City Planning:Technique and Practice---Take,as an example,the control type of planning for the developing area of Chigang in Guangzhou

On the basis of the practice in Guangzhou in recent years,this article proposes the tech-nique of the“control”approach in city planning,and presents its specific application and ex-plorations with the example of the planning for the developing area of Chigang inGuangzhou.With the reform of the urban economic-political system and the advancement of theopen-door policy,significant changes are evolving in the ideas and the ways of city planningand design.To meet the demand of these developments,the new“control”approach in cityplanning and design is thus adopted.

A robust composite wide area control of a DFIG wind energy system for damping inter-area oscillations

This paper presents a novel composite wide area control of a DFIG wind energy system which combines the Robust Exact Differentiator(RED)and Discontinuous Integral(DI)control to damp out inter-area oscillations.RED generates the real-time differentiation of a relative speed signal in a noisy environment while DI control,an extension to a twisting algorithm and PID control,develops a continuous control signal and hence reduces chattering.The proposed control is robust to disturbances and can enhance the overall stability of the system.The proposed composite sliding mode control is evaluated using a modified benchmark two-area power system model with wind energy integration.Simulation results under various operating scenarios show the efficacy of the proposed approach.

Controller area network node reliability assessment based on observable node information

Controller area network(CAN) based fieldbus technologies have been widely used in networked manufacturing systems. As the information channel of the system, the reliability of the network is crucial to the system throughput, product quality, and work crew safety. However, due to the inaccessibility of the nodes' internal states, direct assessment of the reliability of CAN nodes using the nodes' internal error counters is infeasible. In this paper, a novel CAN node reliability assessment method, which uses node's time to bus-off as the reliability measure, is proposed. The method estimates the transmit error counter(TEC) of any node in the network based on the network error log and the information provided by the observable nodes whose error counters are accessible.First, a node TEC estimation model is established based on segmented Markov chains. It considers the sparseness of the distribution of the CAN network errors. Second, by learning the differences between the model estimates and the actual values from the observable node, a Bayesian network is developed for the estimation updating mechanism of the observable nodes. Then, this estimation updating mechanism is transferred to general CAN nodes with no TEC value accessibility to update the TEC estimation. Finally, a node reliability assessment method is developed to predict the time to reach bus-off state of the nodes. Case studies are carried out to demonstrate the effectiveness of the proposed methodology. Experimental results show that the estimates using the proposed model agree well with actual observations.

Modelling the effects of emission control areas on shipping company operations and environmental consequences

In this study,two integrated game models are developed to explore the possible economic and environmental consequences of Emission control areas(ECA)regulations.Moreover,the analytical solutions compared with a benchmark case are derived.We find that vessel speed and SO_(2)emissions will decrease under the ECA regulations.However,shipping company’s level of competition has no effect on the equivalent speed.The equivalent freight volume to be reduced or increased is determined by the additional operational cost per voyage due to ECA regulations.Numerical study and sensitivity analysis reveal that the vessel speed and SO_(2)emission reduction are very sensitive to the inventory costs of intransit cargo.Furthermore,if low-sulphur marine gas oil is used throughout the voyage,the SO_(2)emission reduction may be greater than 80%,with a low impact on the shipping company’s profit.Thus,considering the environmental effects,much stricter limits can be set in the future.