The Center for Hydrometeorology and Remote Sensing at the University of California, Irvine （CHRS） has been collaborating with UNESCO＇s International Hydrological Program （IHP） to build a facility for forecasting ...The Center for Hydrometeorology and Remote Sensing at the University of California, Irvine （CHRS） has been collaborating with UNESCO＇s International Hydrological Program （IHP） to build a facility for forecasting and mitigating hydrological disasters. This collaboration has resulted in the development of the Water and Development Information for Arid Lands-- a Global Network （G-WADI） PERSIANN-CCS GeoServer, a near real-time global precipitation visualization and data service. This GeoServer pro- vides to end-users the tools and precipitation data needed to support operational decision making, research and sound water man- agement. This manuscript introduces and demonstrates the practicality of the G-WADI PERSIANN-CCS GeoServer for monitor- ing extreme precipitation events even over regions where ground measurements are sparse. Two extreme events are analyzed. The first event shows an extreme precipitation event causing widespread flooding in Beijing, China and surrotmding districts on July 21, 2012. The second event shows tropical storm Nock-Ten that occurred in late July of 2011 causing widespread flooding in Thailand. Evaluation of PERSIANN-CCS precipitation over Thailand using a rain gauge network is also conducted and discussed.展开更多
Users of the internet often wish to follow certain news events, and the interests of these users often overlap. General search engines （GSEs） cannot be used to achieve this task due to incomplete coverage and lack o...Users of the internet often wish to follow certain news events, and the interests of these users often overlap. General search engines （GSEs） cannot be used to achieve this task due to incomplete coverage and lack of freshness. Instead, a broker is used to regularly query the built-in search engines （BSEs） of news and social media sites. Each user defines an event profile consisting of a set of query rules called event rules （ERs）. To ensure that queries match the semantics of BSEs, ERs are transformed into a disjunctive normal form, and separated into conjunctive clauses （atomic event rules, AERs）. It is slow to process all AERs on BSEs, and can violate query submission rate limits. Accordingly, the set of AERs is reduced to eliminate AERs that are duplicates, or logically contained by other AERs. Five types of event are selected for experimental comparison and analysis, including natural disasters, accident disasters, public health events, social security events, and negative events of public servants. Using 12 BSEs, 85 ERs for five types of events are defined by five users. Experimental comparison is conducted on three aspects： event rule reduction ratio, number of collected events, and that of related events. Experimental results in this paper show that event rule reduction effectively enhances the efficiency of crawling.展开更多
To better understand the mechanical properties of marble at Jinping II hydropower station, this paper examines the changes of brittle rocks in excavation damaged zones(EDZs) before and after excavation of tunnel with ...To better understand the mechanical properties of marble at Jinping II hydropower station, this paper examines the changes of brittle rocks in excavation damaged zones(EDZs) before and after excavation of tunnel with the tunnel boring machine(TBM). The paper attempts to employ the acoustic emission(AE) to study the AE characteristics and distribution of rockburst before and after TBM-excavated tunnel. It is known that the headrace tunnel #2, excavated by the drill-and-blast(D&B) method, is ahead of the headrace tunnel #3 that is excavated by TBM method. The experimental sub-tunnel #2–1, about 2000 m in depth and 13 m in diameter, between the two tunnels is scheduled. In the experimental sub-tunnel #2–1, a large number of experimental boreholes are arranged, and AE sensors are installed within 10 m apart from the wall of the headrace tunnel #3. By tracking the microseismic signals in rocks, the location, frequency, quantity, scope and intensity of the microseismic signals are basically identifed. It is observed that the AE signals mainly occur within 5 m around the rock wall, basically lasting for one day before tunnel excavation and a week after excavation. Monitoring results indicate that the rockburst signals are closely related to rock stress adjustment. The rock structure has a rapid self-adjustment capacity before and after a certain period of time during tunneling. The variations of rock stresses would last for a long time before reaching a fnal steady state. Based on this, the site-specifc support parameters for the deep tunnels can be accordingly optimized.展开更多
In order to keep decision-makers better informed with emergencies, it is useful to retrieve the user-oriented disaster relevant event information in an aggregated results list through meta-search engine. However, emer...In order to keep decision-makers better informed with emergencies, it is useful to retrieve the user-oriented disaster relevant event information in an aggregated results list through meta-search engine. However, emergent event is dynamic which makes it difficult to use fixed search word or word combinations. This paper proposes an event situation monitoring model（ESMM） event detection model, which realizes heuristic query word vector dynamic expanding by adopting emergency fuzzy scenario reasoning ontology cluster. Disaster event facet information automatic searching is discussed as an example in this paper. The experimental results show that the proposed method can increase accuracy and extra clues not supplied by commercial search engines, which can be used as a supplement information source for government and individuals.展开更多
An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong ...An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong disturbances to the continuous processes and traditional regulatory controllers are unable to eliminate these periodic disturbances. ILMPC integrates the feature of iterative learning control （ILC） handling repetitive signal and the flexibility of model predictive control （MPC）. By on-line monitoring the operation status of batch processes, an event-driven iterative learning algorithm for batch repetitive disturbances is initiated and the soft constraints are adjusted timely as the feasible region is away from the desired operating zone. The results of an industrial application show that the proposed ILMPC method is effective for a class of continuous/batch processes.展开更多
In monitoring Wireless Sensor Networks(WSNs),the traffic usually has bursty characteristics when an event occurs.Transient congestion would increase delay and packet loss rate severely,which greatly reduces network pe...In monitoring Wireless Sensor Networks(WSNs),the traffic usually has bursty characteristics when an event occurs.Transient congestion would increase delay and packet loss rate severely,which greatly reduces network performance.To solve this problem,we propose a Burstiness-aware Congestion Control Protocol(BCCP) for wireless sensor networks.In BCCP,the backoff delay is adopted as a congestion indication.Normally,sensor nodes work on contention-based MAC protocol(such as CSMA/CA).However,when congestion occurs,localized TDMA instead of CSMA/CA is embedded into the nodes around the congestion area.Thus,the congestion nodes only deliver their data during their assigned slots to alleviate the contention-caused congestion.Finally,we implement BCCP in our sensor network testbed.The experiment results show that BCCP could detect area congestion in time,and improve the network performance significantly in terms of delay and packet loss rate.展开更多
The aim of non-intrusive appliance load monitoring （NIALM） is to disaggregate the energy consumption of individual electrical appliances from total power consumption utilizing non-intrusive methods. In this paper, a...The aim of non-intrusive appliance load monitoring （NIALM） is to disaggregate the energy consumption of individual electrical appliances from total power consumption utilizing non-intrusive methods. In this paper, a systematic approach to 0N-0FF event detection and clustering analysis for NIALM were presented. From the aggregate power consumption data set, the data are passed through median filtering to reduce noise and prepared for the event detection algorithm. The event detection algorithm is to determine the switching of ON and OFF status of electrical appliances. The goodness- of-fit （GOF） methodology is the event detection algorithm implemented. After event detection, the events detected were paired into ON-0FF pairing appliances. The results from the ON-OFF pairing algorithm were further clustered in groups utilizing the K-means clustering analysis. The K- means clustering were implemented as an unsupervised learning methodology for the clustering analysis. The novelty of this paper is the determination of the time duration an electrical appliance is turned ON through combination of event detection, ON-OFF pairing and K- means clustering. The results of the algorithm implemen- tation were discussed and ideas on future work were also proposed.展开更多
基金Partial financial support was provided by the NASA-PMM (Grant No. NNX10AK07G)the US Army Research Office project (Grant No. W911NF-11-1-0422)
文摘The Center for Hydrometeorology and Remote Sensing at the University of California, Irvine （CHRS） has been collaborating with UNESCO＇s International Hydrological Program （IHP） to build a facility for forecasting and mitigating hydrological disasters. This collaboration has resulted in the development of the Water and Development Information for Arid Lands-- a Global Network （G-WADI） PERSIANN-CCS GeoServer, a near real-time global precipitation visualization and data service. This GeoServer pro- vides to end-users the tools and precipitation data needed to support operational decision making, research and sound water man- agement. This manuscript introduces and demonstrates the practicality of the G-WADI PERSIANN-CCS GeoServer for monitor- ing extreme precipitation events even over regions where ground measurements are sparse. Two extreme events are analyzed. The first event shows an extreme precipitation event causing widespread flooding in Beijing, China and surrotmding districts on July 21, 2012. The second event shows tropical storm Nock-Ten that occurred in late July of 2011 causing widespread flooding in Thailand. Evaluation of PERSIANN-CCS precipitation over Thailand using a rain gauge network is also conducted and discussed.
文摘Users of the internet often wish to follow certain news events, and the interests of these users often overlap. General search engines （GSEs） cannot be used to achieve this task due to incomplete coverage and lack of freshness. Instead, a broker is used to regularly query the built-in search engines （BSEs） of news and social media sites. Each user defines an event profile consisting of a set of query rules called event rules （ERs）. To ensure that queries match the semantics of BSEs, ERs are transformed into a disjunctive normal form, and separated into conjunctive clauses （atomic event rules, AERs）. It is slow to process all AERs on BSEs, and can violate query submission rate limits. Accordingly, the set of AERs is reduced to eliminate AERs that are duplicates, or logically contained by other AERs. Five types of event are selected for experimental comparison and analysis, including natural disasters, accident disasters, public health events, social security events, and negative events of public servants. Using 12 BSEs, 85 ERs for five types of events are defined by five users. Experimental comparison is conducted on three aspects： event rule reduction ratio, number of collected events, and that of related events. Experimental results in this paper show that event rule reduction effectively enhances the efficiency of crawling.
文摘To better understand the mechanical properties of marble at Jinping II hydropower station, this paper examines the changes of brittle rocks in excavation damaged zones(EDZs) before and after excavation of tunnel with the tunnel boring machine(TBM). The paper attempts to employ the acoustic emission(AE) to study the AE characteristics and distribution of rockburst before and after TBM-excavated tunnel. It is known that the headrace tunnel #2, excavated by the drill-and-blast(D&B) method, is ahead of the headrace tunnel #3 that is excavated by TBM method. The experimental sub-tunnel #2–1, about 2000 m in depth and 13 m in diameter, between the two tunnels is scheduled. In the experimental sub-tunnel #2–1, a large number of experimental boreholes are arranged, and AE sensors are installed within 10 m apart from the wall of the headrace tunnel #3. By tracking the microseismic signals in rocks, the location, frequency, quantity, scope and intensity of the microseismic signals are basically identifed. It is observed that the AE signals mainly occur within 5 m around the rock wall, basically lasting for one day before tunnel excavation and a week after excavation. Monitoring results indicate that the rockburst signals are closely related to rock stress adjustment. The rock structure has a rapid self-adjustment capacity before and after a certain period of time during tunneling. The variations of rock stresses would last for a long time before reaching a fnal steady state. Based on this, the site-specifc support parameters for the deep tunnels can be accordingly optimized.
基金Supported by the National Natural Science Foundation of China(61100133)
文摘In order to keep decision-makers better informed with emergencies, it is useful to retrieve the user-oriented disaster relevant event information in an aggregated results list through meta-search engine. However, emergent event is dynamic which makes it difficult to use fixed search word or word combinations. This paper proposes an event situation monitoring model（ESMM） event detection model, which realizes heuristic query word vector dynamic expanding by adopting emergency fuzzy scenario reasoning ontology cluster. Disaster event facet information automatic searching is discussed as an example in this paper. The experimental results show that the proposed method can increase accuracy and extra clues not supplied by commercial search engines, which can be used as a supplement information source for government and individuals.
基金Supported by the National Creative Research Groups Science Foundation of China （60721062） and the National High Technology Research and Development Program of China （2007AA04Z162）.
文摘An iterative learning model predictive control （ILMPC） technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong disturbances to the continuous processes and traditional regulatory controllers are unable to eliminate these periodic disturbances. ILMPC integrates the feature of iterative learning control （ILC） handling repetitive signal and the flexibility of model predictive control （MPC）. By on-line monitoring the operation status of batch processes, an event-driven iterative learning algorithm for batch repetitive disturbances is initiated and the soft constraints are adjusted timely as the feasible region is away from the desired operating zone. The results of an industrial application show that the proposed ILMPC method is effective for a class of continuous/batch processes.
基金supported in part by National Key Basic Research Program of China(973 program)under Grant No.2007CB307101National Natural Science Foundation of China under Grant No.60833002,60802016,60972010
文摘In monitoring Wireless Sensor Networks(WSNs),the traffic usually has bursty characteristics when an event occurs.Transient congestion would increase delay and packet loss rate severely,which greatly reduces network performance.To solve this problem,we propose a Burstiness-aware Congestion Control Protocol(BCCP) for wireless sensor networks.In BCCP,the backoff delay is adopted as a congestion indication.Normally,sensor nodes work on contention-based MAC protocol(such as CSMA/CA).However,when congestion occurs,localized TDMA instead of CSMA/CA is embedded into the nodes around the congestion area.Thus,the congestion nodes only deliver their data during their assigned slots to alleviate the contention-caused congestion.Finally,we implement BCCP in our sensor network testbed.The experiment results show that BCCP could detect area congestion in time,and improve the network performance significantly in terms of delay and packet loss rate.
文摘The aim of non-intrusive appliance load monitoring （NIALM） is to disaggregate the energy consumption of individual electrical appliances from total power consumption utilizing non-intrusive methods. In this paper, a systematic approach to 0N-0FF event detection and clustering analysis for NIALM were presented. From the aggregate power consumption data set, the data are passed through median filtering to reduce noise and prepared for the event detection algorithm. The event detection algorithm is to determine the switching of ON and OFF status of electrical appliances. The goodness- of-fit （GOF） methodology is the event detection algorithm implemented. After event detection, the events detected were paired into ON-0FF pairing appliances. The results from the ON-OFF pairing algorithm were further clustered in groups utilizing the K-means clustering analysis. The K- means clustering were implemented as an unsupervised learning methodology for the clustering analysis. The novelty of this paper is the determination of the time duration an electrical appliance is turned ON through combination of event detection, ON-OFF pairing and K- means clustering. The results of the algorithm implemen- tation were discussed and ideas on future work were also proposed.
