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Extended food supply chain traceability with multiple automatic identification and data collection technologies.January 2008 (has links)
Hu, Yong. / Thesis submitted in: October 2007. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (p. 127-129). / Abstracts in English and Chinese. / Chapter Chapter 1. --- Introduction --- p.1 / Chapter 1.1. --- Background and Motivation --- p.1 / Chapter 1.2. --- Objectives of the Thesis --- p.3 / Chapter 1.3. --- Scope of the Thesis --- p.6 / Chapter 1.4. --- Structure of the Thesis --- p.6 / Chapter Chapter 2. --- Review of Related Technologies --- p.8 / Chapter 2.1. --- Scope and Requirements of the Supply Chain Traceability --- p.9 / Chapter 2.2. --- Automatic Identification and Data Collection Technologies --- p.14 / Chapter 2.2.1. --- Introduction to the AIDC Technologies --- p.14 / Chapter 2.2.1.1. --- The Barcode --- p.14 / Chapter 2.2.1.2. --- The Radio Frequency Identification (RFID) --- p.17 / Chapter 2.2.1.3. --- The Sensors for Food --- p.19 / Chapter 2.2.1.4. --- The Global Positioning System (GPS) --- p.23 / Chapter 2.2.2. --- Frequencies of the RFID Systems --- p.25 / Chapter 2.2.3. --- Encoding Mechanisms for the RFID Tags and Barcode Labels --- p.30 / Chapter 2.3. --- Standards and Specifications of the EPCglobal --- p.34 / Chapter 2.3.1. --- The EPCglobal Architecture Framework --- p.34 / Chapter 2.3.2. --- The EPCglobal EPCIS Specification --- p.39 / Chapter 2.3.3. --- The EPCglobal Tag Data Standards --- p.42 / Chapter 2.4. --- RFID Applications in Food Supply Chain Management --- p.43 / Chapter 2.5. --- Anti-counterfeit Technologies and Solutions --- p.45 / Chapter 2.6. --- Data Compression Algorithms --- p.47 / Chapter 2.7. --- Shelf Life Prediction Models --- p.49 / Chapter Chapter 3. --- Architecture and Scope of the Application System --- p.54 / Chapter 3.1. --- Application System Architecture --- p.54 / Chapter 3.2. --- Application System Scope --- p.55 / Chapter Chapter 4. --- The Tracking and Tracing Management Module --- p.60 / Chapter 4.1. --- Overview --- p.60 / Chapter 4.2. --- AIDC Technologies Adopted for the Traceable Items --- p.62 / Chapter 4.3. --- Mechanism to Achieve the Nested Visibility --- p.70 / Chapter 4.4. --- Information Integration in the EPCIS --- p.75 / Chapter 4.5. --- Anti-counterfeit Mechanism --- p.82 / Chapter Chapter 5. --- The Storage and Transportation Monitoring Module --- p.90 / Chapter 5.1. --- Overview --- p.90 / Chapter 5.2. --- Compression of the Sensor Data --- p.93 / Chapter 5.3. --- Management of the Sensor Data --- p.95 / Chapter 5.4. --- Responsive Warning Mechanism --- p.102 / Chapter Chapter 6. --- The Sensor Networks Enabled Assessment Module --- p.108 / Chapter 6.1. --- Overview --- p.108 / Chapter 6.2. --- Management of the Sensor Network Data --- p.110 / Chapter 6.3. --- Active Warning Mechanism --- p.114 / Chapter Chapter 7. --- Conclusions --- p.122 / Chapter 7.1. --- Contributions --- p.122 / Chapter 7.2. --- Future Work --- p.124
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An artificial neural network approach to laser-based direct part marking of data matrix symbolsJangsombatsiri, Witaya 08 March 2004 (has links)
Certain applications have recently appeared in industry where a traditional
bar code printed on a label will not survive because the item to be tracked has to be
exposed to harsh environments. Laser direct-part marking is a manufacturing
process used to create permanent marks on a substrate that could help to alleviate
this problem. In this research, a 532 nm laser was utilized to create a direct-part
marked Data Matrix symbol onto carbon steel substrates with different carbon
content. The quality of the laser marked Data Matrix symbol was then evaluated
according to the criteria outlined in the ISO/IEC 16022 bar code technology
specification for Data Matrix.
Several experiments were conducted to explore the effects that different
parameters have on the quality of the laser direct-part marked symbols. First, an
experiment was conducted to investigate the effect of two different laser tool path
patterns. In later experiments, parameters such as type of carbon steel, percent of
laser tool path overlap, profile speed, average power and frequency were found to
have significant effects on the quality of laser direct-part marked Data Matrix
symbols. The analysis of the results indicated that contrast and print growth were
the critical standard performance measures that limited laser direct-part marked
Data Matrix symbols from achieving a higher final grade. No significant effects
were found with respect to other standard performance measures (i.e., encode, axial
uniformity, and unused error correction).
Next, the experimental data collected for contrast and print growth was
utilized as training, validation and testing data sets in the modeling of artificial
neural networks for the laser direct-part marking process. Two performance
measures (i.e., mean squared error and correlation coefficient) were employed to
assess the performance of the artificial neural network models. Single-output
artificial neural network models corresponding to a specific performance measure
were found to have good learning and predicting capabilities. The single-output
artificial neural network models were compared to equivalent multiple linear
regression models for validation purposes. The prediction capability of the single-output
artificial neural network models with respect to laser direct-part marking of
Data Matrix symbols on carbon steel substrates was superior to that of the multiple
linear regression models. / Graduation date: 2004
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Inferring social structure and dominance relationships between rhesus macaques using RFID tracking dataMaddali, Hanuma Teja 22 May 2014 (has links)
This research address the problem of inferring, through Radio-Frequency Identification (RFID) tracking data, the graph structures underlying social interactions in a group of rhesus macaques (a species of monkey). These social interactions are considered as independent affiliative and dominative components and are characterized by a variety of visual and auditory displays and gestures. Social structure in a group is an important indicator of its members’ relative level of access to resources and has interesting implications for an individual’s health. Automatic inference of the social structure in an animal group enables a number of important capabilities, including:
1. A verifiable measure of how the social structure is affected by an intervention such as a change in the environment, or the introduction of another animal, and
2. A potentially significant reduction in person hours normally used for assessing these changes.
The behaviors of interest in the context of this research are those definable using the macaques’ spatial (x,y,z) position and motion inside an enclosure. Periods of time spent in close proximity with other group members are considered to be events of passive interaction and are used in the calculation of an Affiliation Matrix. This represents the strength of undirected interaction or tie-strength between individual animals. Dominance is a directed relation that is quantified using a heuristic for the detection of withdrawal and displacement behaviors. The results of an analysis based on these approaches for a group of 6 male monkeys that were tracked over a period of 60 days at the Yerkes Primate Research Center are presented in this Thesis.
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