近几年“时延(Delay/Latency)”已逐步成为一个重要的传输指标,“低时延”是高品质传输专线的典型需求之一。MS-OTN(Multi-Service Optical Transport Network)网络利用其丰富的开销字节,强大的网络能力和传输速率,能为2Mbps~100Gbps的...近几年“时延(Delay/Latency)”已逐步成为一个重要的传输指标,“低时延”是高品质传输专线的典型需求之一。MS-OTN(Multi-Service Optical Transport Network)网络利用其丰富的开销字节,强大的网络能力和传输速率,能为2Mbps~100Gbps的不同业务类型所承载的高精品用户专线、云间互联、5G等新型业务提供服务。文章通过对MS-OTN网络不同业务封装类型的测试分析比较了各业务封装类型对于时延的影响,进而分析OTN时延影响关键因素,并结合网络部署情况,为各类需求提供出合理的业务选型方案。展开更多
With the emergence of the Internet of Things(IoT), there has been a proliferation of urban studies using big data. Yet, another type of urban research innovations that involve interdisciplinary thinking and methods re...With the emergence of the Internet of Things(IoT), there has been a proliferation of urban studies using big data. Yet, another type of urban research innovations that involve interdisciplinary thinking and methods remains underdeveloped. This paper represents an attempt to adopt a Hidden Markov Model(HMM) toolbox developed in Computer Science for the analysis of eye movement patterns in Psychology to answer urban mobility questions in Geography. The main idea is that both people’s eye movements and travel behavior follow the stop-travel-stop pattern, which can be summarized using HMM. Methodological challenges were addressed by adjusting the HMM to analyze territory-wide travel survey data in Hong Kong, China. By using the adjusted toolbox to identify the activitytravel patterns of working adults in Hong Kong, two distinctive groups of balanced(38.4%) and work-oriented(61.6%) lifestyles were identified. With some notable exceptions, working adults living in the urban core were having a more work-oriented lifestyle. Those with a balanced lifestyle were having a relatively compact zone of non-work activities around their homes but a relatively long commuting distance. Furthermore, working females tend to spend more time at home than their counterparts, regardless of their marital status and lifestyle. Overall, this interdisciplinary research demonstrates an attempt to integrate spatial, temporal, and sequential information for understanding people’s behavior in urban mobility research.展开更多
Poultry behavior monitoring is an important basis for the poultry disease warning.Manual monitoring is mostly used nowadays.In this work,the automatic monitoring system for assisting manual monitoring was examined.Sop...Poultry behavior monitoring is an important basis for the poultry disease warning.Manual monitoring is mostly used nowadays.In this work,the automatic monitoring system for assisting manual monitoring was examined.Sophisticated data mining techniques were used to leverage the data collected by RFID devices.Specifically,(1)weighing sensors and wireless networks of Multiple RFID-tag-collector groups were used to monitor the poultry behavior;(2)RFID tags were putted on individual poultry so that the moving time of the poultry between two RFID-tag-collectors could be recorded.Thus,the characteristic functions of poultry behaviors such as speed,ability to snatch food and resting time could be extracted based on the distance between two RFID-tag-collectors and the relevant time parameters;(3)the sick,normal,active and other poultry groups were categorized by using the K-means method which utilizing the behavior characteristics and poultry weight data in data mining.The results demonstrated that accurate classifications could be obtained according to the poultry characteristics,and the clustering results matched with the results obtained by manual method to identify the poultry groups.Consequently,the technique in this paper has great potential for large-scale poultry disease warning and poultry classification.展开更多
文摘近几年“时延(Delay/Latency)”已逐步成为一个重要的传输指标,“低时延”是高品质传输专线的典型需求之一。MS-OTN(Multi-Service Optical Transport Network)网络利用其丰富的开销字节,强大的网络能力和传输速率,能为2Mbps~100Gbps的不同业务类型所承载的高精品用户专线、云间互联、5G等新型业务提供服务。文章通过对MS-OTN网络不同业务封装类型的测试分析比较了各业务封装类型对于时延的影响,进而分析OTN时延影响关键因素,并结合网络部署情况,为各类需求提供出合理的业务选型方案。
文摘With the emergence of the Internet of Things(IoT), there has been a proliferation of urban studies using big data. Yet, another type of urban research innovations that involve interdisciplinary thinking and methods remains underdeveloped. This paper represents an attempt to adopt a Hidden Markov Model(HMM) toolbox developed in Computer Science for the analysis of eye movement patterns in Psychology to answer urban mobility questions in Geography. The main idea is that both people’s eye movements and travel behavior follow the stop-travel-stop pattern, which can be summarized using HMM. Methodological challenges were addressed by adjusting the HMM to analyze territory-wide travel survey data in Hong Kong, China. By using the adjusted toolbox to identify the activitytravel patterns of working adults in Hong Kong, two distinctive groups of balanced(38.4%) and work-oriented(61.6%) lifestyles were identified. With some notable exceptions, working adults living in the urban core were having a more work-oriented lifestyle. Those with a balanced lifestyle were having a relatively compact zone of non-work activities around their homes but a relatively long commuting distance. Furthermore, working females tend to spend more time at home than their counterparts, regardless of their marital status and lifestyle. Overall, this interdisciplinary research demonstrates an attempt to integrate spatial, temporal, and sequential information for understanding people’s behavior in urban mobility research.
基金Production-study-research Combination projects from the Education Department of Guangdong Province(No.2012B090600052,2012B091100484,2012B040400004,2011A060901027).
文摘Poultry behavior monitoring is an important basis for the poultry disease warning.Manual monitoring is mostly used nowadays.In this work,the automatic monitoring system for assisting manual monitoring was examined.Sophisticated data mining techniques were used to leverage the data collected by RFID devices.Specifically,(1)weighing sensors and wireless networks of Multiple RFID-tag-collector groups were used to monitor the poultry behavior;(2)RFID tags were putted on individual poultry so that the moving time of the poultry between two RFID-tag-collectors could be recorded.Thus,the characteristic functions of poultry behaviors such as speed,ability to snatch food and resting time could be extracted based on the distance between two RFID-tag-collectors and the relevant time parameters;(3)the sick,normal,active and other poultry groups were categorized by using the K-means method which utilizing the behavior characteristics and poultry weight data in data mining.The results demonstrated that accurate classifications could be obtained according to the poultry characteristics,and the clustering results matched with the results obtained by manual method to identify the poultry groups.Consequently,the technique in this paper has great potential for large-scale poultry disease warning and poultry classification.
