Analysis on the Influencing Factors of the Quality Traceable System Established by Edible Agricultural Products Enterprises-Taking Sichuan as an Example

According to the investigation data from 81 edible agricultural products enterprises in Sichuan Province,the influence factors of establishing quality tracing system are empirically analyzed from four aspects,including the enterprise features,the attitudes of operators,management and market competition by using the Logistic model.The results show that the enterprise can establish the quality tracing system after the comprehensive function of a series of internal and external factors.The four factors include peer pressure;age of enterprise;export and the expectation on improving economic interests have the biggest impact on enterprise to establish the quality tracing system.The factors,including the quality safety certificate obtained by the enterprises,export of products,sampling frequency,peer pressure,the pressure from consumers and media,the expectation on improving the competition of products,the expectation on improving economic interests,play a promotion role in helping enterprises to establish quality tracing system.The countermeasures and suggestion are put forward from strengthening the social responsibility of enterprises;intensifying the law enforcement of government and expanding the experimental enterprises with the quality tracing system.

On traceable iterated line graph and hamiltonian path index

Xiong and Liu[21]gave a characterization of the graphs G for which the n-iterated line graph L^(n)(G)is hamiltonian,for n≥2.In this paper,we study the existence of a hamiltonian path in L^(n)(G),and give a characterization of G for which L^(n)(G)has a hamiltonian path.As applications,we use this characterization to give several upper bounds on the hamiltonian path index of a graph.

Application of Blockchain Sharding Technology in Chinese Medicine Traceability System

Traditional Chinese Medicine(TCM)is one of the most promising programs for disease prevention and treatment.Meanwhile,the quality of TCM has garnered much attention.To ensure the quality of TCM,many works are based on the blockchain scheme to design the traceability scheme of TCM to trace its origin.Although these schemes can ensure the integrity,sharability,credibility,and immutability of TCM more effectively,many problems are exposed with the rapid growth of TCM data in blockchains,such as expensive overhead,performance bottlenecks,and the traditional blockchain architecture is unsuitable for TCM data with dynamic growth.Motivated by the aforementioned problems,we propose a novel and lightweight TCM traceability architecture based on the blockchain using sharding(LBS-TCM).Compared to the existing blockchain-based TCM traceability system,our architecture utilizes sharding to develop a novel traceability mechanism that supports more convenient traceability operations for TCM requirements such as uploading,querying,and downloading.Specifically,our architecture consists of a leader shard blockchain layer as its main component,which employs a sharding mechanism to conveniently TCM tracing.Empirical evaluations demonstrated that our architecture showed better performance in many aspects compared to traditional blockchain architectures,such as TCM transaction processing,TCM transaction querying,TCM uploading,etc.In our architecture,tracing TCM has become a very efficient operation,which ensures the quality of TCM and provides great convenience for subsequent TCM analysis and retrospective research.

On-chain is not enough:Ensuring pre-data on the chain credibility for blockchain-based source-tracing systems

The blockchain provides a reliable and scalable method for enabling source-tracing functionality in large-scale Internet of Things(IoT)systems.Traditional blockchain-based source tracing applications are generally based on the hypothesis that the raw data collected by each IoT node are credible and consistent,which however may not always be the truth.As no mechanism ensures the reliability of the original data collected from the IoT devices,these data may be accidently screwed up or maliciously tampered with before they are uploaded on-chain.To address this issue,we propose the Multi-dimensional Certificates of Origin(MCO)method to filter out the potentially incredible data-till all the data uploaded to the chain are credible.To achieve this,we devise the Multidimensional Information Cross-Verification(MICV)and Multi-source Data Matching Calculation(MDMC)methods.MICV verifies whether a to-be-uploaded datum is consistent or credible,and MDMC determines which data should be discarded and which data should be kept to retain the most likely credible/untampered ones in the circumstance when data inconsistency appears.Large-scale experiments show that our scheme ensures on the credibility of data and off the chain with an affordable overhead.

Advances in the Research of Quality Management System of Dairy Enterprises

As the global economy enters a new stage,Chinese dairy enterprises are gradually moving towards the road of internationalization.In this paper,the internationally common quality management system,food safety system and quality traceability system were analyzed and studied to promote the comprehensive transformation and upgrading of dairy industry and broaden the development road with the help of systematic construction.

Impacts of Transparency and Traceability on Fashion Supply Chain System

The level of fashion consumer awareness and communication regarding sustainable consumption is rising. Organizations are working to provide clarity and guidance on fashion consumption. Brands are experimenting with new materials and supply chain strategies, and suppliers are improving the manufacturing processes and quality of products. However, given the size and complexity of the industrial process, these efforts are not adequate in ensuring a sustainable fashion supply chain. Transparency and traceability in the fashion supply chain are needed to improve the fashion industry by supporting sustainable and ethical practices in the apparel supply chain. Key gaps include a lack of comprehensive and transparent information about how, where, and by whom materials are sourced, processed, and assembled;a lack of transparency in the supply chain practices and procedures affects the environment, working conditions, and human health. The industry has to build the capacity to manage its supply chain, more effectively and responsibly, by improving transparency and traceability as the top goals. So, in this context, the main purpose of this research paper is to study the impacts of transparency and traceability on the dimensions of sustainability in fashion supply chain. The researchers have applied descriptive research methods in which secondary data are collected and analyzed through a literature review of peer-reviewed research papers and the primary data are collected through the survey method by distributing a semi structured questionnaire. The data collected are analyzed using statistical tools and techniques. Finally, the results are discussed and presented.

Design and Implementation of Traceability Management System of Agricultural Products Quality and Safety Based on Domestic Basic Software of China

[Objective] To establish the traceability mechanism of agricultural products safety, and the application of promote domestic based software in the supervision area of agricultural products quality and safety. [Method] Through the analysis on the circulation characteristics of agricultural products, like fruits, vegetables, livestock and poultry, the agricultural products quality safety management and traceability query business component libraries were designed. Based on the run-time-supporting environment provided by domestic based software, traceability management system of agricultural products quality and safety was constructed. [Result] The traceability management system provided the information interaction and comprehensive management platform of agricultural product quality and safety based on domestic based software for the government, enterprises and consumers. [Conclusion] Through the application demonstration, the quality control and information traceability of full circulation of agricultural products was achieved effective and reliably, and the management level of agricultural products quality and safety was improved.

Anonymous TollPass: A Blockchain-Based Privacy-Preserving Electronic Toll Payment Model

As big data,Artificial Intelligence,and Vehicle-to-Everything(V2X)communication have advanced,Intelligent Transportation Systems(ITS)are being developed to enable efficient and safe transportation systems.Electronic Toll Collection(ETC),which is one of the services included in ITS systems,is an automated system that allows vehicles to pass through toll plazas without stopping for manual payment.The ETC system is widely deployed on highways due to its contribution to stabilizing the overall traffic system flow.To ensure secure and efficient toll payments,designing a distributed model for sharing toll payment information among untrusted toll service providers is necessary.However,the current ETC system operates under a centralized model.Additionally,both toll service providers and toll plazas know the toll usage history of vehicles.It raises concerns about revealing the entire driving routes and patterns of vehicles.To address these issues,blockchain technology,suitable for secure data management and data sharing in distributed systems,is being applied to the ETC system.Blockchain enables efficient and transparent management of ETC information.Nevertheless,the public nature of blockchain poses a challenge where users’usage records are exposed to all participants.To tackle this,we propose a blockchain-based toll ticket model named AnonymousTollPass that considers the privacy of vehicles.The proposed model utilizes traceable ring signatures to provide unlinkability between tickets used by a vehicle and prevent the identity of the vehicle using the ticket from being identified among the ring members for the ticket.Furthermore,malicious vehicles’identities can be traced when they attempt to reuse tickets.By conducting simulations,we show the effectiveness of the proposed model and demonstrate that gas fees required for executing the proposed smart contracts are only 10%(when the ring size is 50)of the fees required in previous studies.

Geographical origin identification of winter jujube(Ziziphus jujuba Dongzao')by using multi-element fingerprinting with chemometrics

Winter jujube(Ziziphus jujuba'Dongzao')is greatly appreciated by consumers for its excellent quality,but brand infringement frequently occurs in the market.Here,we first determined a total of 38 elements in 167 winter jujube samples from the main winter jujube producing areas of China by inductively coupled plasma mass spectrometer(ICP-MS).As a result,16 elements(Mg,K,Mn,Cu,Zn,Mo,Ba,Be,As,Se,Cd,Sb,Ce,Er,Tl,and Pb)exhibited significant differences in samples from different producing areas.Supervised linear discriminant analysis(LDA)and orthogonal projection to latent structures discriminant analysis(OPLS-DA)showed better performance in identifying the origin of samples than unsupervised principal component analysis(PCA).LDA and OPLS-DA had a mean identification accuracy of 87.84 and 94.64%in the testing set,respectively.By using the multilayer perceptron(MLP)and C5.0,the prediction accuracy of the models could reach 96.36 and 91.06%,respectively.Based on the above four chemometric methods,Cd,Tl,Mo and Se were selected as the main variables and principal markers for the origin identification of winter jujube.Overall,this study demonstrates that it is practical and precise to identify the origin of winter jujube through multi-element fingerprint analysis with chemometrics,and may also provide reference for establishing the origin traceability system of other fruits.

FADSF:A Data Sharing Model for Intelligent Connected Vehicles Based on Blockchain Technology

With the development of technology,the connected vehicle has been upgraded from a traditional transport vehicle to an information terminal and energy storage terminal.The data of ICV(intelligent connected vehicles)is the key to organically maximizing their efficiency.However,in the context of increasingly strict global data security supervision and compliance,numerous problems,including complex types of connected vehicle data,poor data collaboration between the IT(information technology)domain and OT(operation technology)domain,different data format standards,lack of shared trust sources,difficulty in ensuring the quality of shared data,lack of data control rights,as well as difficulty in defining data ownership,make vehicle data sharing face a lot of problems,and data islands are widespread.This study proposes FADSF(Fuzzy Anonymous Data Share Frame),an automobile data sharing scheme based on blockchain.The data holder publishes the shared data information and forms the corresponding label storage on the blockchain.The data demander browses the data directory information to select and purchase data assets and verify them.The data demander selects and purchases data assets and verifies them by browsing the data directory information.Meanwhile,this paper designs a data structure Data Discrimination Bloom Filter(DDBF),making complaints about illegal data.When the number of data complaints reaches the threshold,the audit traceability contract is triggered to punish the illegal data publisher,aiming to improve the data quality and maintain a good data sharing ecology.In this paper,based on Ethereum,the above scheme is tested to demonstrate its feasibility,efficiency and security.

Uncertainty-Aware Deep Learning: A Promising Tool for Trustworthy Fault Diagnosis

Recently,intelligent fault diagnosis based on deep learning has been extensively investigated,exhibiting state-of-the-art performance.However,the deep learning model is often not truly trusted by users due to the lack of interpretability of“black box”,which limits its deployment in safety-critical applications.A trusted fault diagnosis system requires that the faults can be accurately diagnosed in most cases,and the human in the deci-sion-making loop can be found to deal with the abnormal situa-tion when the models fail.In this paper,we explore a simplified method for quantifying both aleatoric and epistemic uncertainty in deterministic networks,called SAEU.In SAEU,Multivariate Gaussian distribution is employed in the deep architecture to compensate for the shortcomings of complexity and applicability of Bayesian neural networks.Based on the SAEU,we propose a unified uncertainty-aware deep learning framework(UU-DLF)to realize the grand vision of trustworthy fault diagnosis.Moreover,our UU-DLF effectively embodies the idea of“humans in the loop”,which not only allows for manual intervention in abnor-mal situations of diagnostic models,but also makes correspond-ing improvements on existing models based on traceability analy-sis.Finally,two experiments conducted on the gearbox and aero-engine bevel gears are used to demonstrate the effectiveness of UU-DLF and explore the effective reasons behind.

A GAN-EfficientNet-Based Traceability Method for Malicious Code Variant Families

Due to the diversity and unpredictability of changes in malicious code,studying the traceability of variant families remains challenging.In this paper,we propose a GAN-EfficientNetV2-based method for tracing families of malicious code variants.This method leverages the similarity in layouts and textures between images of malicious code variants from the same source and their original family of malicious code images.The method includes a lightweight classifier and a simulator.The classifier utilizes the enhanced EfficientNetV2 to categorize malicious code images and can be easily deployed on mobile,embedded,and other devices.The simulator utilizes an enhanced generative adversarial network to simulate different variants of malicious code and generates datasets to validate the model’s performance.This process helps identify model vulnerabilities and security risks,facilitating model enhancement and development.The classifier achieves 98.61%and 97.59%accuracy on the MMCC dataset and Malevis dataset,respectively.The simulator’s generated image of malicious code variants has an FID value of 155.44 and an IS value of 1.72±0.42.The classifier’s accuracy for tracing the family of malicious code variants is as high as 90.29%,surpassing that of mainstream neural network models.This meets the current demand for high generalization and anti-obfuscation abilities in malicious code classification models due to the rapid evolution of malicious code.

Antenna Design of Traceability System in Pig Breeding Stage

[Objective] In response to pig breeding stage characteristics,the research aimed to design the traceability system to realize the pig product marking which based on RFID technology. [Method] The antenna＇s design method of electronic tag and reader antenna were expounded and different antennas were used for testing communication test of RFID system. [Result] When the parameter setup such as data transportation ratio was same,the communication distance of external antenna was farther than RCB antenna; compare with three external antennas,the communication distance of coaxial antenna and wall-hanged antenna were farther. In 500 kbps transfer rate,communication distance was within 28 meters,and in 250 kbps transfer rate,communication distance was within 40 meters. Considered the cost of hardware,the price of wall-hanged antenna was higher than coaxial antenna,so in the same communication distance request,system selected coaxial antenna. [Conclusion] During the pig breeding stage,by dint of electronic tag and reader designed by the research could improve the safety of the pork and fully realize the track of source of food and provide technology support for the transparent management of food safety.

Potentials and Challenges of Carbon Knowledge Graph in Sustainable Textile Production for Carbon Traceability:A Review

Textile production has received considerable attention owing to its significance in production value,the complexity of its manufacturing processes and the extensive reach of its supply chains.However,textile industry consumes substantial energy and materials and emits greenhouse gases that severely harm the environment.In addressing this challenge,the concept of sustainable production offers crucial guidance for the sustainable development of the textile industry.Low-carbon manufacturing technologies provide robust technical support for the textile industry to transition to a low-carbon model by optimizing production processes,enhancing energy efficiency and minimizing material waste.Consequently,low-carbon manufacturing technologies have gradually been implemented in sustainable textile production scenarios.However,while research on low-carbon manufacturing technologies for textile production has advanced,these studies predominantly concentrate on theoretical methods,with relatively limited exploration of practical applications.To address this gap,a thorough overview of carbon emission management methods and tools in textile production,as well as the characteristics and influencing factors of carbon emissions in key textile manufacturing processes is presented to identify common issues.Additionally,two new concepts,carbon knowledge graph and carbon traceability,are introduced,offering strategic recommendations and application directions for the low-carbon development of sustainable textile production.Beginning with seven key aspects of sustainable textile production,the characteristics of carbon emissions and their influencing factors in key textile manufacturing process are systematically summarized.The aim is to provide guidance and optimization strategies for future emission reduction efforts by exploring the carbon emission situations and influencing factors at each stage.Furthermore,the potential and challenges of carbon knowledge graph technology are summarized in achieving carbon traceability,and several research ideas and suggestions are proposed.

Study on Pork Quality and Safety Traceability System and Relevant Management Systems

It is the key to construct the traceability mechanism of quality responsibility for ensuring the quality and safety of animal products. In this study, after defining the concept of traceability system and analyzing its function mechanism, the design ideas of pork quality and safety traceability system based on bar code and Internet were put forward, including network structure, system process, business process and information identifica- tion. Then the relevant management systems were proposed.

Modern Corrosion Mapping of Storage Tank Bottoms--Notable Advancements in Critical Zone Coverage,Inspection Efficiency and Data Integrity

Every day,an NDT(Non-Destructive Testing)report will govern key decisions and inform inspection strategies that could affect the flow of millions of dollars which ultimately affects local environments and potential risk to life.There is a direct correlation between report quality and equipment capability.The more able the equipment is-in terms of efficient data gathering,signal to noise ratio,positioning,and coverage-the more actionable the report is.This results in optimal maintenance and repair strategies providing the report is clear and well presented.Furthermore,when considering tank floor storage inspection it is essential that asset owners have total confidence in inspection findings and the ensuing reports.Tank floor inspection equipment must not only be efficient and highly capable,but data sets should be traceable and integrity maintained throughout.Corrosion mapping of large surface areas such as storage tank bottoms is an inherently arduous and time-consuming process.MFL(magnetic flux leakage)based tank bottom scanners present a well-established and highly rated method for inspection.There are many benefits of using modern MFL technology to generate actionable reports.Chief among these includes efficiency of coverage while gaining valuable information regarding defect location,severity,surface origin and the extent of coverage.More recent advancements in modern MFL tank bottom scanners afford the ability to scan and record data sets at areas of the tank bottom which were previously classed as dead zones or areas not scanned due to physical restraints.An example of this includes scanning the CZ(critical zone)which is the area close to the annular to shell junction weld.Inclusion of these additional dead zones increases overall inspection coverage,quality and traceability.Inspection of the CZ areas allows engineers to quickly determine the integrity of arguably the most important area of the tank bottom.Herein we discuss notable developments in CZ coverage,inspection efficiency and data integrity that combines to deliver an actionable report.The asset owner can interrogate this report to develop pertinent and accurate maintenance and repair strategies.

Research Progress and Prospects of Traceability Methods of Organic Matter in Lake Sediment

Organic matter in sediment is an important carrier of energy and material circulation in ecosystems,and also provides an important place for the accumulation of nutrient salts.The study of its composition,structure and characteristics is of great importance for the study of the geochemical cycle of sediment in water environment.Identifying the source of organic matter in sediment and mastering its temporal and spatial distribution characteristics are important ways to reveal the migration and transformation law of pollutants,which is conducive to controlling nutrient load from the source and providing strong technical support for the fine management of water environment.

Research of Blockchain Technology in the Traceability of Characteristic Agricultural Products

With the increasingly prominent problem of food safety,the quality traceability of characteristic agricultural products has become a pressing issue.This study focuses on the application of blockchain technology in the traceability of characteristic agricultural products,aiming to explore its potential and practical value in improving the efficiency and transparency of the traceability system of agricultural products.Through the combination of case analysis and model construction,a blockchain-based traceability system for characteristic agricultural products was established.The results showed that the traceability system could effectively record the whole process information of agricultural products from production and processing to sales,and greatly improve the immutability and traceability of data.Lastly,this paper also points out that the use of blockchain technology can improve the market trust in characteristic agricultural products,provide consumers with authentic and reliable product information,and provide new technical means for the quality management of agricultural products.

Fabrication and measurement of traceable pitch standard with a big area at trans-scale

Atom lithography with chromium can be utilized to fabricate a pitch standard, which is chrectly traceable to me wavelength of the laser standing waves. The result of a calibrated commercial AFM measurement demonstrates that the pitch standard is （212.8±0.1） nm with a peak-to-valley-height （PTVH） better than 20 nm. The measurement results show the high period accuracy of traceability with the standing laser wavelength （λ/2 = 212.78 nm）. The Cr nano-grating covers a 1000μm×500 μm area, with a PTVH better than 10 nm. The feature width broadening of the Cr nanostructure has been experimentally observed along the direction of the standing waves. The PTVH along the Gaussian laser direction is similar to a Gaussian distribution. Highly uniform periodic nanostructures with a big area at the millimeter scale, and the surface growth uniformity of the Cr nano-grating, show its great potential in the application of a traceable pitch standard at trans-scales.

Research on the Consumers Willingness to Buy Traceable Pork with Different Quality Information:A Case Study of Consumers in Weifang, Shandong Province

The traceability system can effectively reduce the food safety risks, however, it is confronted with various problems during its implementation. In this context, the paper carries out a case study of consumers in Weifang, Shandong Province, and studies their willingness to pay the traceable pork with different quality information. The results indicate that, the consumers show high expectations towards the introduction of traceability system, and they tend to buy the traceable pork only with breeding and slaughter information; their behaviors of purchase are greatly influenced by the following factors: the consumers education, age, income, attention on food safety and whether there are pregnant family members, etc..