Described and exemplified a semantic scoring system of students' on-line English-Chinese translation. To achieve accurate assessment, the system adopted a comprehensive method which combines semantic scoring with ...Described and exemplified a semantic scoring system of students' on-line English-Chinese translation. To achieve accurate assessment, the system adopted a comprehensive method which combines semantic scoring with keyword matching scoring. Four kinds of words-verbs, adjectives, adverbs and "the rest" including nouns, pronouns, idioms, prepositions, etc., are identified after parsing. The system treats different words tagged with different part of speech differently. Then it calculated the semantic similarity between these words of the standard versions and those of students' translations by the distinctive differences of the semantic features of these words with the aid of HowNet. The first semantic feature of verbs and the last semantic features of adjectives and adverbs are calculated. "The rest" is scored by keyword matching. The experiment results show that the semantic scoring system is applicable in fulfilling the task of scoring students' on-line English-Chinese translations.展开更多
Estimation of the sample position is essential for working process monitoring and management in the life science automation laboratory.Bluetooth low-energy(BLE)beacons have the advantages of low price,small size and l...Estimation of the sample position is essential for working process monitoring and management in the life science automation laboratory.Bluetooth low-energy(BLE)beacons have the advantages of low price,small size and low energy consumption,which make them a promising solution for sample position estimation in the automated laboratory.Several fingerprinting models have been proposed to achieve indoor localization with the received signal strength(RSS)data.However,most of the research depends on intensive beacon installation.Proximity estimation,which depends entirely on one beacon,is more suitable for sample position estimation in large automated laboratories.The complexity of the life science automation laboratory environment brings challenges to the traditional path loss model(PLM),which is a widely used radio wave propagation model-based proximity estimation method.In this paper,BLE sensing devices for sample position estimation are proposed.The BLE beacon-based proximity estimation is discussed in the framework of machine learning,in which the support vector regression(SVR)is utilized to model the nonlinear relationship between the RSS data and distance,and the Kalman filter is utilized to decrease the RSS data deviation.The experimental results over different environments indicate that the SVR outperforms the PLM significantly,and provides 1 m absolute errors for more than 95%of the testing samples.The Kalman filter brings benefits to stable distance predictions.Apart from proximity-based sample position estimation,the proposed framework turned out to be effective in position estimation between parallel workbenches and position estimation on an automated workstation.展开更多
This paper presents an automated testing network system for paper laboratory based on CAN bus. The overall architecture, hardware interface and software function are discussed in detail. It is indicated through experi...This paper presents an automated testing network system for paper laboratory based on CAN bus. The overall architecture, hardware interface and software function are discussed in detail. It is indicated through experiment that the system can collect, analyze and store the test results from the various measuring instruments in the paper lab automatically. The simple, reliable, low-cost measuring automation system will have a prosperous application in the future paper industry.展开更多
This paper considers an on-line scheduling and routing problem concerning the automated storage and retrieval system from tobacco industry. In this problem, stacker cranes run on one common rail between two racks. Mul...This paper considers an on-line scheduling and routing problem concerning the automated storage and retrieval system from tobacco industry. In this problem, stacker cranes run on one common rail between two racks. Multiple input/output-points are located at the bottom of the racks. The stacker cranes transport bins between the input/output-points and cells on the racks to complete requests generated over time. Each request should be accomplished within its response time. The objective is to minimize the time by which all the generated requests are completed. Under a given physical layout, the authors study the complexity of the problem and design on-line algorithms for both one-stacker-crane model and two-stacker-crane model. The algorithms axe validated by instances and numerical simulations.展开更多
The increasing use of mobile robots in laboratory settings has led to a higher degree of laboratory automation.However,when mobile robots move in laboratory environments,mechanical errors,environmental disturbances an...The increasing use of mobile robots in laboratory settings has led to a higher degree of laboratory automation.However,when mobile robots move in laboratory environments,mechanical errors,environmental disturbances and signal interruptions are inevitable.This can compromise the accuracy of the robot’s localization,which is crucial for the safety of staff,robots and the laboratory.A novel time-series predicting model based on the data processing method is proposed to handle the unexpected localization measurement of mobile robots in laboratory environments.The proposed model serves as an auxiliary localization system that can accurately correct unexpected localization errors by relying solely on the historical data of mobile robots.The experimental results demonstrate the effectiveness of this proposed method.展开更多
基金The National Natural Science Foundution of China(No60496326)The Second Phase of 985 Project of Shanghai Jiaotong University
文摘Described and exemplified a semantic scoring system of students' on-line English-Chinese translation. To achieve accurate assessment, the system adopted a comprehensive method which combines semantic scoring with keyword matching scoring. Four kinds of words-verbs, adjectives, adverbs and "the rest" including nouns, pronouns, idioms, prepositions, etc., are identified after parsing. The system treats different words tagged with different part of speech differently. Then it calculated the semantic similarity between these words of the standard versions and those of students' translations by the distinctive differences of the semantic features of these words with the aid of HowNet. The first semantic feature of verbs and the last semantic features of adjectives and adverbs are calculated. "The rest" is scored by keyword matching. The experiment results show that the semantic scoring system is applicable in fulfilling the task of scoring students' on-line English-Chinese translations.
基金the Synergy Project ADAM(Autonomous Discovery of Advanced Materials)funded by the European Research Council(Grant No.856405).
文摘Estimation of the sample position is essential for working process monitoring and management in the life science automation laboratory.Bluetooth low-energy(BLE)beacons have the advantages of low price,small size and low energy consumption,which make them a promising solution for sample position estimation in the automated laboratory.Several fingerprinting models have been proposed to achieve indoor localization with the received signal strength(RSS)data.However,most of the research depends on intensive beacon installation.Proximity estimation,which depends entirely on one beacon,is more suitable for sample position estimation in large automated laboratories.The complexity of the life science automation laboratory environment brings challenges to the traditional path loss model(PLM),which is a widely used radio wave propagation model-based proximity estimation method.In this paper,BLE sensing devices for sample position estimation are proposed.The BLE beacon-based proximity estimation is discussed in the framework of machine learning,in which the support vector regression(SVR)is utilized to model the nonlinear relationship between the RSS data and distance,and the Kalman filter is utilized to decrease the RSS data deviation.The experimental results over different environments indicate that the SVR outperforms the PLM significantly,and provides 1 m absolute errors for more than 95%of the testing samples.The Kalman filter brings benefits to stable distance predictions.Apart from proximity-based sample position estimation,the proposed framework turned out to be effective in position estimation between parallel workbenches and position estimation on an automated workstation.
文摘This paper presents an automated testing network system for paper laboratory based on CAN bus. The overall architecture, hardware interface and software function are discussed in detail. It is indicated through experiment that the system can collect, analyze and store the test results from the various measuring instruments in the paper lab automatically. The simple, reliable, low-cost measuring automation system will have a prosperous application in the future paper industry.
基金supported by the National Natural Science Foundation of China under Grant No.11371137Research Fund for the Doctoral Program of China under Grant No.20120074110021
文摘This paper considers an on-line scheduling and routing problem concerning the automated storage and retrieval system from tobacco industry. In this problem, stacker cranes run on one common rail between two racks. Multiple input/output-points are located at the bottom of the racks. The stacker cranes transport bins between the input/output-points and cells on the racks to complete requests generated over time. Each request should be accomplished within its response time. The objective is to minimize the time by which all the generated requests are completed. Under a given physical layout, the authors study the complexity of the problem and design on-line algorithms for both one-stacker-crane model and two-stacker-crane model. The algorithms axe validated by instances and numerical simulations.
文摘The increasing use of mobile robots in laboratory settings has led to a higher degree of laboratory automation.However,when mobile robots move in laboratory environments,mechanical errors,environmental disturbances and signal interruptions are inevitable.This can compromise the accuracy of the robot’s localization,which is crucial for the safety of staff,robots and the laboratory.A novel time-series predicting model based on the data processing method is proposed to handle the unexpected localization measurement of mobile robots in laboratory environments.The proposed model serves as an auxiliary localization system that can accurately correct unexpected localization errors by relying solely on the historical data of mobile robots.The experimental results demonstrate the effectiveness of this proposed method.
