Traceability Information Research Articles

Blockchain adoption and contract coordination driven by supplier encroachment and retail service: An analysis from consumers’ information traceability awareness

This study constructs a supply chain consisting of a supplier with online encroachment and a retailer with retail service in the presence of consumers' information traceability awareness. We first establish two scenarios, without blockchain technology scenario and with blockchain technology scenario, and derive the equilibrium solutions. Next, we respectively analyze the effects of consumers' information traceability awareness, the sharing proportion of information traceability cost for the supplier, and the matching degree between retail service and consumers’ taste on the equilibrium solutions. Then, we derive the conditions of blockchain adoption in the supply chain. Finally, with the target of improving the profitability of the supply chain after adopting blockchain technology, we propose several coordination contracts to achieve Pareto improvement.

Design of Meat Product Safety Information Chain Traceability System Based on UHF RFID.

As a result of the current imperfection of the meat traceability system, there have been numerous food safety events with serious consequences. In this paper, a meat product information traceability system is designed to efficiently prevent such problems. This system develops an identification tag information reader based on ultra-high frequency (UHF) Radio Frequency Identification (RFID). It is compatible with LoRa wireless, USB serial port, RS485, and RJ45 Ethernet connection. Among them, the efficiency analysis of the Q-value algorithm finds that the recognition rate of the system reaches a maximum of about 0.367 when the number of tags n is about the frame length. The multi-tag anti-collision algorithm design based on the algorithm improves the efficiency of information collection in production and distribution links. The traceability code identification scheme is designed to effectively match various links, and the platform of system is built using LabVIEW2014 software, which has five sub-modules including user management, farm management, slaughter management, logistics management, and sales management. The system uses MySQL databases to store traceability information so that users can complete their queries by entering the traceability code on the system platform. The system not only has a low cost and a broad range of applications, but it also realizes the tracking record of meat product traceability information from breeding to selling, completes the function from information collection to information inquiry, and solves the problem of the incomplete traceability information chain. In addition, the system not only enhances the informational transparency of meat products in the product supply chain but also provides information for the regulatory authorities to effectively monitor safety.

Blockchain adoption and application in closed‐loop production under information asymmetry

AbstractAlthough the decentralization and traceability features of blockchain technology are crucial for fostering closed‐loop production, there are numerous obstacles and insufficient incentives for its implementation. This paper constructs the analysis framework of blockchain adoption and application in closed‐loop production, including four parts: blockchain adoption incentive contract, condition analysis of blockchain application, revenue analysis of blockchain application, and information screening analysis of blockchain application. It is found that the adoption incentive contract is an important driving force to promote manufacturer to apply blockchain technology, and the manufacturer needs to pay information rent to the consumer under information asymmetry. The manufacturer can obtain consumer traceability preference and realize information screening between the manufacturer and consumer. Consumer traceability preference for new products can better promote traceable information technology level and closed‐loop revenue. This research is of great significance in promoting sustainable closed‐loop production.

An Intelligent Task Scheduling Model for Hybrid Internet of Things and Cloud Environment for Big Data Applications

One of the most significant issues in Internet of Things (IoT) cloud computing is scheduling tasks. Recent developments in IoT-based technologies have led to a meteoric rise in the demand for cloud storage. In order to load the IoT services onto cloud resources efficiently even while satisfying the requirements of the applications, sophisticated planning methodologies are required. This is important because several processes must be well prepared on different virtual machines to maximize resource usage and minimize waiting times. Different IoT application tasks can be difficult to schedule in a cloud-based computing architecture due to the heterogeneous features of IoT. With the rise in IoT sensors and the need to access information quickly and reliably, fog cloud computing is proposed for the integration of fog and cloud networks to meet these demands. One of the most important necessities in a fog cloud setting is efficient task scheduling, as this can help to lessen the time it takes for data to be processed and improve QoS (quality of service). The overall processing time of IoT programs should be kept as short as possible by effectively planning and managing their workloads, taking into account limitations such as task scheduling. Finding the ideal approach is challenging, especially for big data systems, because task scheduling is a complex issue. This research provides a Deep Learning Algorithm for Big data Task Scheduling System (DLA-BDTSS) for the Internet of Things (IoT) and cloud computing applications. When it comes to reducing energy costs and end-to-end delay, an optimized scheduling model based on deep learning is used to analyze and process various tasks. The method employs a multi-objective strategy to shorten the makespan and maximize resource consumption. A regional exploration search technique improves the optimization algorithm’s capacity to exploit data and avoid becoming stuck in local optimization. DLA-BDTSS was compared to other well-known task allocation methods in accurate trace information and the CloudSim tools. The investigation showed that DLA-BDTSS performed better than other well-known algorithms. It converged faster than different approaches, making it beneficial for big data task scheduling scenarios, and it obtained an 8.43 percent improvement in the outcomes. DLA-BDTSS obtained an 8.43% improvement in the outcomes with an execution time of 34 s and fitness value evaluation of 76.8%.

Construction of a Human Resource Sharing System Based on Blockchain Technology

Human resource data sharing is very important for the cooperation of human resource institutions. Since the human resource data-sharing service needs to take into account the needs of individuals and talent service institutions, it faces issues such as the security of information sharing and the traceability of information. Therefore, this paper constructs a human resource data-sharing service system based on blockchain technology. Its trust mechanism is based on the Fabric alliance chain, and the system makes full use of its advantages of decentralization and consensus. Our research mainly includes data sharing architecture design, consensus mechanism analysis, smart contract design, data sharing process, and blockchain construction. The contribution of this paper is mainly in two aspects. On the one hand, it explores the trust mechanism of human resource data sharing and gives the scheme of the Fabric alliance chain. On the other hand, the overall architecture and smart contract design are given on the construction of the blockchain, which provides a reference for future research on human resource data sharing.

Research on Traceability of Agricultural Product Supply Chain Information

Traceability of agricultural product supply chain information has become an important issue due to increasing concerns about food safety and quality. In this paper, we propose a traceability system that utilizes blockchain technology to ensure the transparency and integrity of agricultural product supply chain information. The system includes a data collection and storage module, a blockchain-based traceability module, and a user interface module. We tested the system on a case study of a tomato supply chain, and the results show that the system is effective in tracing the entire supply chain and detecting anomalies. The proposed traceability system can provide consumers with reliable information about the origin and quality of agricultural products, and can also help producers and distributors to improve their supply chain management.

Determining the Authenticity of Labeled Traceability Information by DNA Identity Test for Hanwoo Meats Distributed in Seoul, Korea

Determining the Authenticity of Labeled Traceability Information by DNA Identity Test for Hanwoo Meats Distributed in Seoul, Korea

BdLT-Seq as a barcode decay-based method to unravel lineage-linked transcriptome plasticity

Cell plasticity is a core biological process underlying a myriad of molecular and cellular events taking place throughout organismal development and evolution. It has been postulated that cellular systems thrive to balance the organization of meta-stable states underlying this phenomenon, thereby maintaining a degree of populational homeostasis compatible with an ever-changing environment and, thus, life. Notably, albeit circumstantial evidence has been gathered in favour of the latter conceptual framework, a direct observation of meta-state dynamics and the biological consequences of such a process in generating non-genetic clonal diversity and divergent phenotypic output remains largely unexplored. To fill this void, here we develop a lineage-tracing technology termed Barcode decay Lineage Tracing-Seq. BdLT-Seq is based on episome-encoded molecular identifiers that, supported by the dynamic decay of the tracing information upon cell division, ascribe directionality to a cell lineage tree whilst directly coupling non-genetic molecular features to phenotypes in comparable genomic landscapes. We show that cell transcriptome states are both inherited, and dynamically reshaped following constrained rules encoded within the cell lineage in basal growth conditions, upon oncogene activation and throughout the process of reversible resistance to therapeutic cues thus adjusting phenotypic output leading to intra-clonal non-genetic diversity.

Features and characteristics of business intelligence (BI)-systems as a tool for improving the efficiency of company activities

In the era of the information economic development of society, which is based on the digitalization of communication technologies and software for business administration algorithms, business analytics occupies an important place, a tool for obtaining high-quality, unique, and expensive information, maintaining the global competitive advantages of projects in the face of long-term force majeure risks of the viability of the economy. Since the middle of the last century, information technologies have been in constant development, gradually being introduced into all spheres and strata of society: production, accounting and analytical support, management, analysis, forecasts, risks. This paper considers the tools of digital business transformation and trends within the new knowledge paradigm based on a controlled understanding of the value properties of an information product. The successful use of business intelligence can indicate an increase in the success of the company and the country's competitiveness in the global market. Business analytics of companies is currently undergoing a stage of reengineering due to testing various programs, understanding, and analyzing the database, improving communication interaction at all levels of business processes, and making decisions in conditions of interactivity and transparency. The state of traceability and transparency of information, evolution and dynamics of conclusions and proposals over a long period of the company's activity in the sectoral and global aspect is of value. The features, characteristics, and functions of business intelligence (BI) systems as a tool for increasing the efficiency of the company's activities are analyzed. Business intelligence systems were considered as a tool for data analysis and processing, a comparative analysis of modern business intelligence systems and market trends of business intelligence systems was conducted, because of which the role of BI systems in increasing the efficiency of the company's activities was revealed. Keywords: business analytics, business data analysis, data integration, data presentation, IT sphere, company performance.

Enhanced Multiset Consensus Protocol Based on PBFT for Logistics Information Traceability

In the recent years, the global logistics industry has greatly driven the development of the world economy. At the same time, a large amount of data information is generated. Due to the frequent occurrence of logistics information leakage and forgery, it is necessary to find solutions that can accurately trace logistics information and ensure the security and authenticity of logistics information. The birth of blockchain technology has transformed the logistics industry from quantitative change to qualitative change. The technical characteristics of blockchain technology, such as distributed storage ideas, decentralization, immutability, and complex encryption consensus algorithm, endow it with a wide range of application prospects in the logistics industry. This paper proposes an enhanced multiset consensus algorithm based on PBFT (practical Byzantine fault tolerance) for logistics information traceability and storage on the logistics blockchain. The application of the proposed multi-set consensus algorithm in the topology structure composed of multiple sets can improve the consensus efficiency of logistics information in the blockchain. We improve consensus capability and transaction speed, avoid redundant consensus message packets occupying a large bandwidth, and efficiently process logistics information generated at any time. We ensure the traceability of logistics information and achieve efficient and accurate traceability, and the efficiency and security of the proposed algorithm are analyzed. This paper aims to solve the problems of traceability, trustworthiness, and efficient processing of blockchain applications in logistics information to operate the logistics network efficiently. This paper compares the proposed algorithm with the PBFT-related expansion algorithm regarding bandwidth occupation, delay, and throughput. The results show that the MPBFT consensus algorithm significantly improves the efficiency of the logistics blockchain network.

Genomic Epidemiology of Severe Acute Respiratory Syndrome Coronavirus 2 Transmission Among University Students in Western Pennsylvania.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) control on college campuses is challenging given communal living and student social dynamics. Understanding SARS-CoV-2 transmission among college students is important for the development of optimal control strategies. SARS-CoV-2 nasal swab samples were collected from University of Pittsburgh students for symptomatic testing and asymptomatic surveillance from August 2020 through April 2021 from 3 campuses. Whole-genome sequencing (WGS) was performed on 308 samples, and contact tracing information collected from students was used to identify transmission clusters. We identified 31 Pangolin lineages of SARS-CoV-2, the majority belonging to B.1.1.7 (Alpha) and B.1.2 lineages. Contact tracing identified 142 students (46%) clustering with each other; WGS identified 53 putative transmission clusters involving 216 students (70%). WGS identified transmissions that were missed by contact tracing. However, 84 cases (27%) could not be linked by either WGS or contact tracing. Clusters were most frequently linked to students residing in the same dormitory, off-campus roommates, friends, or athletic activities. The majority of SARS-CoV-2-positive samples clustered by WGS, indicating significant transmission across campuses. The combination of WGS and contact tracing maximized the identification of SARS-CoV-2 transmission on campus. WGS can be used as a strategy to mitigate, and further prevent transmission among students.

Internet of Everything and Digital Twin enabled Service Platform for Cold Chain Logistics

The proliferation of the e-commerce market has posed challenges to staff safety, product quality, and operational efficiency, especially for cold chain logistics (CCL). Recently, the logistics of vaccine supply under the worldwide COVID-19 pandemic rearouses public attention and calls for innovative solutions to tackle the challenges remaining in CCL. Accordingly, this study proposes a cyber-physical platform framework applying the Internet of Everything (IoE) and Digital Twin (DT) technologies to promote information integration and provide smart services for different stakeholders in the CCL. In the platform, reams of data are generated, gathered, and leveraged to interconnect and digitalize physical things, people, and processes in cyberspace, paving the way for digital servitization. Deep learning techniques are used for accident identification and indoor localization based on Bluetooth Low Energy (BLE) to actualize real-time staff safety supervision in the cold warehouse. Both algorithms are designed to take advantage of the IoE infrastructure to achieve online self-adapting in response to surrounding evolutions. Besides, with the help of mobile and desktop applications, paperless operation for shipment, remote temperature and humidity (T&H) monitoring, anomaly detection and warning, and customer interaction are enabled. Thus, information traceability and visibility are highly fortified in this way. Finally, a real-life case study is conducted in a pharmaceutical distribution center to demonstrate the feasibility and practicality of the proposed platform and methods. The dedicated hardware and software are developed and deployed on site. As a result, the effectiveness of staff safety management, operational informatization, product quality assurance, and stakeholder loyalty maintenance shows a noticeable improvement. The insights and lessons harvested in this study may spark new ideas for researchers and inspire practitioners to meet similar needs in the industry.

Perceived Value of Information Attributes: Accounting for Consumer Heterogeneous Preference and Valuation for Traceable Agri-Food

Information attributes characterize traceable agri-food. The perceived value of information attributes influences consumers' preferences for traceable agri-food, consisting of two dimensions, predictive value and confidence value. We examine heterogeneous preferences and willingness to pay (WTP) in China's traceable agri-food market. Using the choice experiments, we explore how the traceability information, certification type, region of origin, and price influence Chinese consumers' Fuji apple choices. We identify three consumer classes by a latent class model: certification-oriented class (65.8%), price-sensitive and origin-oriented class (15.0%), and no-buy class (19.2%). The results show that consumer sociodemographic characteristics, predictive value, and confidence value are the heterogeneous sources that determine their preferences for Fuji apple information attributes. Specifically, consumers' age, family income per month, and whether the family has children under 18 significantly impact the membership probability of consumers in both certification-oriented and price-sensitive and origin-oriented classes. Consumers' predicted value and confidence value significantly impact the membership probability of consumers in the certification-oriented class. In contrast, consumers' predicted value and confidence value have no significant impact on the membership probability of consumers in price-sensitive and origin-oriented class.

Traceability Management System Using Blockchain Technology and Cost Estimation in the Metrology Field.

Metrological traceability is essential to ensure the reliability of calibration tests. Calibration certificates usually include information on only one upper-level reference standard. As metrological traceability is multi-layered, generally there is no method available for end users to instantly confirm the traceability from the reference standard to a primary standard. This study focuses on the Ethereum blockchain, which has both tamper resistance and high availability, as a digital data management method. To improve the transparency and reliability of calibration tests, a smart contract that traces back to the primary standard is proposed. Consequently, it is confirmed that end users can instantly obtain traceability information. In addition, the execution of smart contracts requires transaction fees. Here, the calculation of the transaction fees is organized, and the traceability management system is discussed from a cost-effective perspective in the field of metrology.

Tracking disclosure change trajectories for financial fraud detection

The global economic disruption brought by COVID‐19 crisis can set a stage for the prevalence of financial statement frauds, which jeopardize the efficient functioning of capital markets. In this paper, we propose a nuanced method to detect frauds by tracking granular changes in disclosures over time. Specifically, we first align paragraphs between consecutive disclosures by their similarities. This alignment can be solved as an optimization‐based matching problem. Then we identify three types of changed contents: recurrent, newly added, and deleted contents. For each type, we measure the changes in terms of fraud‐relevant linguistics features, such as sentiment and uncertainties. Further, we formulate a firm's Management Discussion and Analysis change trajectory over years as a multivariate time series composed of these granular metrics. We implement a deep learning model to predict frauds using the change trajectory as an input. Extensive experiments demonstrate that our model significantly outperforms benchmark models, and its performance increases with the length of the change trajectory. Moreover, we found specific types of changes are strongly associated with frauds, including weak modal or reward words in newly added or deleted contents. Our work provides an optimization‐based method to define change trajectories and trace information mutation in narratives. Finally, our study contributes to the fraud detection literature with a new predictive signal—disclosure change trajectories with an effective deep learning architecture.

A Novel Blockchain-Enabled Supply-Chain Management Framework for Xinjiang Jujube: Research on Optimized Blockchain Considering Private Transactions.

Excellent jujube supply-chain management is of great significance to the development of the Xinjiang jujube industry. However, traditional jujube supply-chain management is faced with the dilemmas of opaque connection of transaction flow and capital flow information, unreliable product traceability information, and jujube farmers' lack of bargaining power. In this research, we propose a jujube supply-chain-management framework based on blockchain. Hyperledger fabric is the distributed solution platform of this research. The current blockchain-based traceability framework for agri-food emphasizes the construction process and ignores the performance and characteristics of the framework. This research optimizes the blockchain-network-topology architecture and storage cost of writing data. This not only solves the traceability of jujube, but also fills the gap in previous research on the traceability framework. Moreover, transactions are innovatively divided into common transactions and private transactions. Private transactions have enhanced the bargaining power of jujube farmers. Through the analysis of benchmark tests, the effectiveness and feasibility of the framework are verified.

Blockchain-Based Secure Traceable Scheme for Food Supply Chain

The typical food traceability system’s data layer is made up of relational databases managed by core businesses, which cannot ensure data security. It is inefficient and requires a lot of upkeep. The food supply chain has numerous actors, making it difficult for consumers to safeguard their rights when purchasing food with quality issues. Due to the numerous organizations involved in the food supply chain, food safety monitoring and traceability have become challenging. The supply chain’s major organizations have control and administrative authority over the data under the current food traceability system, which is overly centralized for traceability information. The safety and dependability of food may be ensured by using the food traceability system to track food information. We can witness a series of detailed insights into food from the manufacturing source to the consumption terminal. A blockchain-based food tracking system is created as a solution to these issues. On the Ethereum platform, the system was created. It was also employed in the blockchain system, in addition to its features of decentralization, tamper-proof, and traceability. To implement the data update service and the food recall function, introduce the Food and Drug Administration node. Consumers have the option to not only enquire about food traceability throughout the manufacturing process but also to file complaints regarding the traceability system’s rights protection.

An Artwork Rental System Based on Blockchain Technology

In recent years, due to the slowdown of the global economy and the instability of the stock market and real estate market, the art market has gradually become the third-largest investment market after the former two. As more and more funds flow into the art market, the two seemingly unrelated industries, art, and finance have increasingly close cooperation due to the growing prosperity of the art market. As a very important part of the process of art financialization, the development of art banks has also received extensive attention from all walks of life. In addition, blockchain, as a technology to jointly maintain reliable databases through trustlessness and decentralization, has grown rapidly in recent years, and is gradually applied in various fields. The advantages of blockchain technology are decentralization, anonymity, immutability, and traceability of stored information. The proposed scheme applies the characteristics of blockchain technology to Art Bank’s art rental system, and will have the following advantages: the use of Hyperledger technology, various art banks being merged into an alliance, and information among alliance members being shared, which is convenient for tenants to comprehensively query a single item. Using blockchain technology, in an environment where there is no central authority, under the premise of preventing the tampering of artwork-related information, ensures that the detailed information of the artwork is shared. Traditional leasing agreements can be compiled into smart contract leasing contracts to automatically run and manipulate data. The proposed protocol satisfies the following security requirements: identities’ mutual authentication, non-repudiation between every two parties, and other major security requirements based on blockchain. When a dispute arises, our proposed scheme also has an arbitration mechanism to clarify responsibilities.

Pandemic Response Officers: Integration Between Medical, Public Health, and Higher Education Systems to Expedite Prevention and Response.

Research and policy studies alike have enumerated population and community health benefits of system integration between medical, public health, and social entities. The emergence of the COVID-19 pandemic revealed the necessity of a well-trained and adequately staffed public health and medical workforce in order to process SARS-CoV-2 cases and prevent subsequent transmission. Higher education systems, in particular, represented defined populations of exposure and transmission. Opportunities existed for collaboration and task sharing between institutions of higher education and local public health departments to limit spread and impacts. This article describes the Pandemic Response Officer (PRO) program at Cornell University, a team of staff and students created during the intensity of the pandemic to benefit the Tompkins County and Cornell University communities. The PRO program was formed in January 2021, with an original team of 8 individuals, working iteratively to investigate and support employee cases and exposures. Implementation was motivated by Cornell University's dual responsibility as a large employer that also possessed SARS-CoV-2 test results of employees. PROs loaded case information into a shared HIPPA-compliant electronic record that collected information for case notification, case investigation, isolation support, contact tracing, contact notification, and quarantine support. Over time, the PROs grew to a team of 25, gaining responsibilities as university and public health systems shared roles to maximize resources. From January 1 to December 31, 2021, PROs managed 773 employee and 2943 student cases. During the Omicron surge (November 28-December 31, 2021), PROs saved the public health department an estimated 2797 hours of effort, equating to more than 10 professionals working full-time, evenings and weekends, to process cases and contacts during this interval. By integrating efforts between a university and public health agency, this intervention minimized SARS-CoV-2 transmission via expedient case support and alleviated strain on public health systems by expanding the public health workforce.

A bibliometric and content analysis of technological advancement applications in agricultural e-commerce

Given the severe difficulties and challenges being faced during the current COVID-19 pandemic, agribusinesses must consider alternative means to market and sell agriproducts using e-commerce and advanced technologies. Agricultural e-commerce that utilizes advanced technologies can promote sustainable economic growth and gender equality and, therefore, helps achieve the Sustainable Development Goals. It also allows farmers access to new markets where they can bypass intermediaries, leading to higher income, less waste, and fresher produce for customers. The usefulness of using agricultural e-commerce depends on the efficiency of addressing the emerging challenges from merging perspectives of agricultural and e-commerce fields. Literature reviews addressed both fields from different perspectives, however, most literature addresses the agriculture and e-commerce fields separately, leading to unclarity in understanding the differences between agriproducts and other products. This study aims to present a comprehensive and robust roadmap of technological advancements and challenges in agricultural e-commerce through a thorough bibliometric and content analysis and provide a conceptual architecture for best practices. The bibliometric and content analysis sheds light on the agricultural e-commerce categories, challenges, and limitations. This study identifies the most influential research and topic trends, determines the topical discipline areas, and provides visions and directions for future research in the field of agricultural e-commerce. It discusses the challenges of agricultural e-commerce and agriproducts and how advanced technologies help solve such challenges. This study summarises the best practice implementation of agricultural e-commerce by providing strong logistics, implementing standardization, including information knowledge of agriproducts, and creating a traceability information system. The result of this paper is presented as a proposed conceptual architecture for agricultural e-commerce that addresses the abovementioned best practice concepts and utilizes the Blockchain and IoT technologies to provide innovative solutions for the agricultural e-commerce stakeholders. Finally, this study provides prospects for future research on advanced technologies in agricultural e-commerce.