Xiaoshuan Zhang

Developing WSN-based traceability system for recirculation aquaculture

Aquaculture has moved from conventional open systems to high density and highly productive land-based recirculation systems. Consumers have increased consumption of fish and fish products due to recognition of their nutritional value along with social progress and the improvement of living standards. A traceability system is considered as an effective tool to guarantee safety in fish products and improve the supply chain transparency. This paper developed a Wireless Sensor Network (WSN) based Traceability System for Recirculation Aquaculture (RATS). System tests shows that the WSN-based traceability system has comparable data accuracy and advantage of easy installment and configuration.

A hybrid reasoning mechanism integrated evidence theory and set pair analysis in Swine-Vet

Swine-Vet is a kind of a web-based expert system for swine disease diagnosis and has been promoted in north of China past 3years. The few issues relevant with low diagnosis efficiency and error have arisen during the system test and promotion due to the limitation of previous adopted reasoning techniques and immaturity of diagnosis domain knowledge. This paper proposes a hybrid multimodal reasoning mechanism to resolve the swine intercurrent diseases and improve the system diagnosis efficiency. The framework consists of two modules: one is the forward diagnosing module, information fusion method based on evidence theory is used to solve the barriers of syndrome in swine diagnosis field, and the other is the backward confirming module, set pair analysis (SPA) is adopted to resolve evidence conflict and distinguish uncertain and unknown symptom information during the process of diagnosis. Then, in order to demonstrate this model, a case study is given. Finally, the benefits and challenges of the hybrid multimodal reasoning application in expert system are discussed.

Evaluation of learner adoption intention of e‐learning in China: A methodology based on perceived innovative attributes

Abstract E‐learning, as an innovative and alternative way of distance learning, provides a strong challenge to traditional learning with its unique advantage. This paper, on the diffusion of e‐learning adoption in China, investigates peoples perceptions and attitudes toward adopting e‐learning, and explores the factors affecting the e‐learning adoption behaviour from an innovation adoption perspective. Based on the model of Rogers’ innovation adoption theory, every factor of perceived innovative attributes influencing the individual adoption behaviour, namely perceived relative advantage, perceived compatibility, perceived trialability, and perceived observability, will be analysed to test the relationship between the perceived innovative attributes and adoption intention of e‐learning. The result shows that the four perceived innovative attributes do have certain influences on peoples adoption of e‐learning.

Development and evaluation on a wireless multi-gas-sensors system for improving traceability and transparency of table grape cold chain

A WGS2 for table grape cold chain was developed and evaluated.The key traceability indicators include temperature, humidity, CO2, O2, and SO2.The shelf life model was built to predict the quality indicators.Tested and analyzed in two sample table grapes cold chains in China.Improving the traceability and transparency of the table grape cold chain. There is increasing requirement to improve traceability and transparency of table grapes cold chain. Key traceability indicators including temperature, humidity and gas microenvironments (e.g., CO2, O2, and SO2) based on table grape cold chain management need to be monitored and controlled. This paper presents a Wireless Multi-Gas-Sensors System (WGS2) as an effective real-time cold chain monitoring system, which consists of three units: (1) the WMN which applies the 433MHz as the radio frequency to increase the transmission performance and forms a wireless sensor network; (2) the WAN which serves as the intermediary to connect the users and the sensor nodes to keep the sensor data without delay by the GPRS remote transmission module; (3) the signal processing unit which contains embedded software to drive the hardware to normal operation and shelf life prediction for table grapes. Then the study evaluates the WGS2 in a cold chain scenario and analyses the monitoring data. The results show that the WGS2 is effective in monitoring quality, and improving transparency and traceability of table grape cold chains. Its deploy ability and efficiency in implantation can enable the establishment of a more efficient, transparent and traceable table grape supply chain.

MS-BWME: a wireless real-time monitoring system for brine well mining equipment.

This paper describes a wireless real-time monitoring system (MS-BWME) to monitor the running state of pumps equipment in brine well mining and prevent potential failures that may produce unexpected interruptions with severe consequences. MS-BWME consists of two units: the ZigBee Wireless Sensors Network (WSN) unit and the real-time remote monitoring unit. MS-BWME was implemented and tested in sampled brine wells mining in Qinghai Province and four kinds of indicators were selected to evaluate the performance of the MS-BWME, i.e., sensor calibration, the systems real-time data reception, Received Signal Strength Indicator (RSSI) and sensor node lifetime. The results show that MS-BWME can accurately judge the running state of the pump equipment by acquiring and transmitting the real-time voltage and electric current data of the equipment from the spot and provide real-time decision support aid to help workers overhaul the equipment in a timely manner and resolve failures that might produce unexpected production down-time. The MS-BWME can also be extended to a wide range of equipment monitoring applications.

Evaluation on home storage performance of table grape based on sensory quality and consumers’ satisfaction

With continuous rise of table grapes consumption and increased public awareness of food safety, the quality control of grapes in storage after purchase is not sufficiently examined. Home storage constitutes the last and important stage in grape supply chain. Literature review shows that few researches on grape quality focus on the home storage stage compared with numerous researches reported on the quality control during postharvest and transportation process. This paper reports the performance evaluation of grape quality at home storage and consumers’ satisfaction using integrated sensory evaluations. The internal attributes, including Texture, Taste and Odor of the table grapes and the appearance indices, Color and Cleanliness are examined. Key results show that during home storage, all the internal attributes decrease rapidly as time goes on, and cleanliness and color appear to be deteriorating in a lower speed. A comprehensive quality index was created to measure the quality of table grape which has high correlation with the Overall acceptability perceived by consumers.

Development and evaluation of an intelligent traceability system for frozen tilapia fillet processing

BACKGROUND The main export varieties in China are brand-name, high-quality bred aquatic products. Among them, tilapia has become the most important and fast-growing species since extensive consumer markets in North America and Europe have evolved as a result of commodity prices, year-round availability and quality of fresh and frozen products. As the largest tilapia farming country, China has over one-third of its tilapia production devoted to further processing and meeting foreign market demand. RESULTS Using by tilapia fillet processing, this paper introduces the efforts for developing and evaluating ITS-TF: an intelligent traceability system integrated with statistical process control (SPC) and fault tree analysis (FTA). Observations, literature review and expert questionnaires were used for system requirement and knowledge acquisition; scenario simulation was applied to evaluate and validate ITS-TF performance. CONCLUSION The results show that traceability requirement is evolved from a firefighting model to a proactive model for enhancing process management capacity for food safety; ITS-TF transforms itself as an intelligent system to provide functions on early warnings and process management by integrated SPC and FTA. The valuable suggestion that automatic data acquisition and communication technology should be integrated into ITS-TF was achieved for further system optimization, perfection and performance improvement.

Ontology Based Vegetable Supply Chain Knowledge Expressing

Ontology is widely researched in knowledge engineering, AI etc. and some domain ontologies have been put forward recently. In this paper, through analyzing the current situation of China agricultural supply chain informationization, we discuss the using of ontology in vegetable supply chain knowledge expressing. We put forward a process to build vegetable supply chain Ontology and give a vegetable supply chain knowledge expressing frame. The frame can be used to express concepts and their relationships of vegetable supply chain as well as build vegetable supply chain knowledge base.

FARMERS' INFORMATION USAGE INTENTION IN CHINA BASED ON THE TECHNOLOGY ACCEPTANCE MODEL

Information technology acceptance has received much attention, but little research has been conducted to assess farmers’ information adoption. Despite the importance of information, its value will not be realized if farmers are reluctant to accept it. This research aims to study farmers’ information adoption in China, in order to provide some decision-making advice for the people and organization who supply the agriculture information. The model of information usage intention has been established based on the Technology Acceptance Model (TAM). A sample of 231 farmers participated in this study. The results show that the factors which influence the usage willingness for information are perceived usefulness, perceived ease of use, learning intention, risk preference and experience in information before. In addition, income and education may also affect the decision.

Using Support Vector Machines to Predict the Variation of Organic Pollutants in Pond Water

There is a growing perception that the research of fishery water quality forecasting are popular and important topic today, due to the food quality security and health impact caused by exposing to water pollutants existing in aquaculture. This paper aims to prove the feasibility of predicting the organic pollutant levels of pond water via SVM. The experimental data in weekly time series are collected from the fishery ponds in Xiao Tangshan in Beijing. The functional characteristics, including the network structure, the kernel function selection and the parameter sensitivity of SVM are investigated. The performance of the SVM model and the conventional BP neural network in predicting is also compared.