Improving traceability and transparency of table grapes cold chain logistics by integrating WSN and correlation analysis

Xiao, Xinqing; He, Qi; Li, Zhigang; Antoce, Arina Oana; Zhang, Xiaoshuan

doi:10.1016/j.foodcont.2016.11.019

Cited by 68 publications

(25 citation statements)

References 40 publications

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“…The study of correlation is a method that uses the relevant two sets of variables to reflect the overall relevance. The Pearson correlation coefficient represents the degree of linear correlation between the two sets of variables [56]. The Pearson correlation coefficient R can be expressed as a formula:…”

Section: Correlation Analysismentioning

confidence: 99%

Bearing Fault Feature Selection Method Based on Weighted Multidimensional Feature Fusion

Dai

Zhang

2020

IEEE Access

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Rolling bearing is one of the most critical components in rotating machinery, so in order to efficiently select features, reduce feature dimensions and improve the correctness of fault diagnosis, a feature selection and fusion method based on weighted multi-dimensional feature fusion is proposed. Firstly, features are extracted from different domains to constitute the original high-dimensional feature set. Considering the large number of invalid and redundant features contained in such original feature set, a feature selection process that combines with support vector machine (SVM) single feature evaluation, correlation analysis and principal component analysis-weighted load evaluation (PCA-WLE) is put forward in this paper for selecting sensitive features. The selected features are weighted and fused according to their sensitivity so as to further weaken the interference of low important features. Finally, this process is applied to the data provided by the Case Western Reserve University Bearing Data Center and Xi'an Jiaotong University School of Mechanical Engineering, respectively, and the fault is diagnosed by using the particle swarm optimization-support vector machine (PSO-SVM). The results show that this method can accurately identify different fault categories and degrees of bearing, which is superior and practical than single-domain fault diagnosis with higher recognition ability. INDEX TERMS Features selection, feature weighting, sensitive features, fault diagnosis.

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Section: Correlation Analysismentioning

confidence: 99%

Bearing Fault Feature Selection Method Based on Weighted Multidimensional Feature Fusion

Dai

Zhang

2020

IEEE Access

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“…Other articles discussed the introduction of the Internet of Things and analysis methods based on it [22,23]. According to this analysis, the introduction of tracking and tracing technologies is an important step towards a uniform information base across a network [20,21,[23][24][25]. Also of high importance in the field of action for transparency is the use of decision-making tools that provide the decision maker with information permitting a more transparent decision-making process [26,27].…”

Section: Optimizing Processesmentioning

confidence: 99%

Fields of Action for Designing Measures to Avoid Food Losses in Logistics Networks

Kleineidam

2020

Sustainability

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The literature contains many analyses of measures against food loss. However, there exists no structured analysis of the objective of these measures. This study employs a systematic literature analysis and open expert interviews, combining the perspectives of science and practice. For each analyzed case, we identified the objectives behind the implemented measures. Using qualitative clustering, we categorized the located objectives into fields of action. The identified 13 fields of action provide an overview of the objectives of food loss prevention measures. The results indicate that different levels of importance can be assigned to these fields of action. In particular, the results show the relevance of increased network cooperation and transparency within a company and along the entire value chain. Furthermore, the study indicates that the creation of transparency provides the greatest overall added value in terms of reducing food losses.

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“…To apply FSM in managing the state of logistics object in logistics context and realize the ALST, the primary step is to determine the states and events of the objects and their relationships in the logistics process [10][11][12]. The possible states of every logistics object in the logistics process are given as follows: initial state (s), termination state (e), normal state (n), vehicle loading (o), unqualified environment indicator, delayed delivery (t), cargo loss (i), wrong loading (w), waiting process (ew), and exception handling.…”

Section: Fsm-based Active Tracking System In Logistics Contextmentioning

confidence: 99%

A Logistics Status Real-time Tracking System Based on Wireless Sensor Network

Chen

2018

Int. J. Onl. Eng.

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Abstract-The progress in the economic society has driven the rapid development of the logistics industry. In the face of increasingly enormous and complicated logistics systems, it is of great practical significance to study how to effectively control the logistics process, minimize the labour cost and provide real-time monitoring data for users. For this purpose, this paper designs an active logistics status tracking (ALST) system platform based on Wireless sensor network (WSN). This paper, by fully integrating the characteristics of WSN, designs the system architecture based on the design philosophy of active logistics status tracking method; it also constructs and realizes the hardware function modules such as wireless sensor node, vehicle gateway, user terminal and backend server etc., and adopts the finite-state machine (FSM)-based active tracking model to maintain the logistics object status; and then it carries out programming of wireless sensor node active state tracking in TinyOS2.x, and finally performs system test under normal operation. The active logistics status tracking system can be widely applied in the logistics industry, to optimize the logistics process, reduce losses and improve logistics operation efficiency.Keywords-wireless sensor network (WSN), active logistics status tracking (ALST), finite-state machine (FSM), tinyos.2 IntroductionWith the increasingly complex logistics system nowadays, it is of great significance to study how to effectively control the logistics process, save labour costs and provide real-time monitoring data for users [1][2]. In the traditional logistics tracking method, the centralized control and optimization methods were often applied, which could optimize the operation of logistics system to some degree, but cannot satisfy the monitoring demands of the rapidly changing logistics system due to its technical limitations [3][4]. Now, in terms of information acquisition and network deployment, the WSN has been freed from the limitations of infrastructures in the traditional network, and can be customized to the demands of logistics operation. Compared with the traditional technology, it can not only collect and transmit data, but also perceive the status information of things and surrounding environment with certain computing 58

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Improving traceability and transparency of table grapes cold chain logistics by integrating WSN and correlation analysis

Cited by 68 publications

References 40 publications

Bearing Fault Feature Selection Method Based on Weighted Multidimensional Feature Fusion

Bearing Fault Feature Selection Method Based on Weighted Multidimensional Feature Fusion

Fields of Action for Designing Measures to Avoid Food Losses in Logistics Networks

A Logistics Status Real-time Tracking System Based on Wireless Sensor Network

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