Event detection from text data is an active area of research. While the emphasis has been on event identification and labeling using a single data source, this work considers event and story line detection when using ...
详细信息
ISBN:
(纸本)9781509052073
Event detection from text data is an active area of research. While the emphasis has been on event identification and labeling using a single data source, this work considers event and story line detection when using a large number of data sources. In this setting, it is natural for different events in the same domain, e.g. violence, sports, politics, to occur at the same time and for different story lines about the same event to emerge. To capture events in this setting, we propose an algorithm that detects events and story lines about events for a target domain. Our algorithm leverages a multi-relational sentence level semantic graph and well known graph properties to identify overlapping events and story lines within the events. We evaluate our approach on two large data sets containing millions of news articles from a large number of sources. Our empirical analysis shows that our approach improves the detection precision and recall by 10% to 25%, while providing complete event summaries.
Robustness of prediction models is an essential requirement for cancer related diagnostic and prognostic studies. A reliable prognosis of breast cancer is very much dependent on accurate identification of the diagnose...
详细信息
ISBN:
(纸本)9781509012862
Robustness of prediction models is an essential requirement for cancer related diagnostic and prognostic studies. A reliable prognosis of breast cancer is very much dependent on accurate identification of the diagnosed cases. Predictive analytics and learning based methods have shown to provide an effective framework for prognostic studies by accurately classifying data instances into the relevant set of classes based on the severity of the tumor. However a performance validation check is an important analysis to be carried out for benchmarking the best performing variants of a predictive model. This study assesses the relative performance of different variants of a supervised learning algorithm that is used quite commonly to implement a pattern-recognition based model for prognostic assessment of breast cancer data. Principal components analysis performs the pre-processing stage and extracts the most relevant set of features for training different types of decision trees that learn the patterns in the data for classification of new instances. The data of diagnostic cases from the original Wisconsin breast cancer database has been used in the study. Major algorithms under the decision tree family of techniques namely CART and C4.5 have been implemented under different platforms like WEKA, Python and Matlab to evaluate the comparative performance of each other. A major finding has been the low degree of sensitivity of classification accuracy to feature reduction in the case of this data and the same has been investigated and reported.
Unmanned aerial vehicles (UAVs) can be used to provide wireless network and remote surveillance coverage for disaster-affected areas. During such a situation, the UAVs need to return periodically to a charging station...
详细信息
ISBN:
(纸本)9781509015412
Unmanned aerial vehicles (UAVs) can be used to provide wireless network and remote surveillance coverage for disaster-affected areas. During such a situation, the UAVs need to return periodically to a charging station for recharging, due to their limited battery capacity. We study the problem of minimizing the number of UAVs required for a continuous coverage of a given area, given the recharging requirement. We prove that this problem is NP-complete. Due to its intractability, we study partitioning the coverage graph into cycles that start at the charging station. We first characterize the minimum number of UAVs to cover such a cycle based on the charging time, the traveling time, and the number of subareas to be covered by the cycle. Based on this analysis, we then develop an efficient algorithm, the cycles with limited energy algorithm. The straightforward method to continuously cover a given area is to split it into N subareas and cover it by N cycles using N additional UAVs. Our simulation results examine the importance of critical system parameters: the energy capacity of the UAVs, the number of subareas in the covered area, and the UAV charging and traveling times. We demonstrate that the cycles with limited energy algorithm requires 69%-94% fewer additional UAVs relative to the straightforward method, as the energy capacity of the UAVs is increased, and 67%-71% fewer additional UAVs, as the number of subareas is increased.
In recent years, with the extensive application of the path planning technology, the development prospect of this technology is more and more broad, and the scientific research value of it is also more and more import...
详细信息
ISBN:
(纸本)9781509035595
In recent years, with the extensive application of the path planning technology, the development prospect of this technology is more and more broad, and the scientific research value of it is also more and more important. It is very necessary to apply it to the underground coal mine with complex terrain, and the algorithm is the core content of the research on path planning. We add simulated annealing algorithm into the process of ant colony algorithm formed simulated annealing ant colony algorithm in this paper, and apply it to the path planning, solve the local optimum problem caused by precocity in ant colony algorithm. For further ensure to find the optimal path, entropy increase strategy was used, that means using multiple update path to avoid algorithm premature, it's easier to find global optimal solution. Simulation result shows that the method presented in this paper obtains the optimization path and proves that the algorithm is efficient and reliable.
In allusion to the deficiency of existing methods in moving target detection for transmission lines under complex background, we proposed a method for realizing automatic moving target detection. Adopting the field im...
详细信息
In allusion to the deficiency of existing methods in moving target detection for transmission lines under complex background, we proposed a method for realizing automatic moving target detection. Adopting the field images with moving target which were taken from the transmission lines anti-theft warning system of a power company in Xinjiang, and choosing the background difference as the object detection algorithm, Gaussian mixture model (GMM) was used for real-time update of background model, through subtracting the updated background image from the current image, we can obtain the foreground moving target. Then, the OTSU algorithm was adopted to complete the image segmentation of moving target area, and marked the foreground moving target in transmission lines filed image to realize the automatic detection for moving target. The results show that the combination of background difference and Gaussian Mixture Background Modeling is sensitive to the change of complex background image, so the complex background can be timely updated and all the foreground moving targets can be automatically extracted from transmission lines images with complex background, showing that the proposed method is applicable for automatically detection of moving target in transmission lines under complex background.
High-level synthesis for FPGA designs (FPGA-HLS) is recently required in various applications. Since wire delays are becoming a design bottleneck in FPGA, we need to handle interconnection delays and clock skews in FP...
详细信息
ISBN:
(纸本)9781467394994
High-level synthesis for FPGA designs (FPGA-HLS) is recently required in various applications. Since wire delays are becoming a design bottleneck in FPGA, we need to handle interconnection delays and clock skews in FPGA-HLS flow. In this paper, we propose an FPGA-HLS algorithm optimizing critical path with interconnection-delay and clock-skew consideration. By utilizing HDR architecture, we floorplan circuit modules in HLS flow and, based on the result, estimate interconnection delays and clock skews. To reduce the critical-path delay(s) of a circuit, we propose two novel methods for FPGA-HLS. Experimental results demonstrate that our algorithm can improve circuit performance by up to 24% compared with conventional approaches.
In this paper, a new approach based on Binary Black Hole algorithm (BBHA) and Adaptive Boosting version Ml (AdaboostM1) is proposed for finding genes that can classify the group of cancers correctly. In this approach,...
详细信息
In this paper, a new approach based on Binary Black Hole algorithm (BBHA) and Adaptive Boosting version Ml (AdaboostM1) is proposed for finding genes that can classify the group of cancers correctly. In this approach, BBHA is used to perform gene selection and AdaboostM1 with 10-fold cross validation is adopted as the classifier. Also, to find the relation between the biomarkers for biological point of view, decision tree algorithm (C4.5) is utilized. The proposed approach is tested on three benchmark microarrays. The experimental results show that our proposed method can select the most informative gene subsets by reducing the dimension of the data set and improve classification accuracy as compared to several recent studies.
In this paper, we present a self-optimizing routing algorithm using local information only, in a three-dimensional (3D) virtual grid network. A virtual grid network is a well-known network model for its ease of design...
详细信息
ISBN:
(纸本)9781509026562
In this paper, we present a self-optimizing routing algorithm using local information only, in a three-dimensional (3D) virtual grid network. A virtual grid network is a well-known network model for its ease of designing algorithms and saving energy consumption. We consider a 3D virtual grid network which is obtained by virtually dividing a network into a set of unit cubes called cells. There is one specific node named a router at each cell, and each router is connected with the routers at adjacent cells. This implies that each router can communicate with 6 routers. We suppose one special node (named a source node) and one moving node (named a destination node) in a 3D virtual grid networks. We consider maintenance of an inter-cell communication path to a destination node from a source node. We propose an optimizing protocol in a 3D virtual grid network, which can transform an arbitrary given path (from a source node to a destination node) to the optimal (shortest) path using only local information (6 hops: 3 hops each back and forward along the routing path) of each router.
Wearables have emerged as a revolutionary technology in many application domains including healthcare and fitness. Machine learning algorithms, which form the core intelligence of wearables, traditionally deduce a com...
详细信息
ISBN:
(纸本)9781467390064
Wearables have emerged as a revolutionary technology in many application domains including healthcare and fitness. Machine learning algorithms, which form the core intelligence of wearables, traditionally deduce a computational model from a set of training examples to detect events of interest (e.g. activity type). However, in the dynamic environment in which wearables typically operate in, the accuracy of a computational model drops whenever changes in configuration of the system (such as device type and sensor orientation) occur. Therefore, there is a need to develop systems which can adapt to the new configuration autonomously. In this paper, using transfer learning as an organizing principle, we develop several algorithms for data mapping. The data mapping algorithms employ effective signal similarity methods and are used to adapt the system to the new configuration. We demonstrate the efficacy of the data mapping algorithms using a publicly available dataset on human activity recognition.
In this paper Field Programmable Gate Array (FPGA) system level based methodology for control system design is proposed and described in details on the case study of three-axis positioning controller implementation. S...
详细信息
ISBN:
(纸本)9781509021628
In this paper Field Programmable Gate Array (FPGA) system level based methodology for control system design is proposed and described in details on the case study of three-axis positioning controller implementation. System level design tool, such as Xilinx System Generator (XSG), provides Simulink based FPGA design and automatic converting of XSG model into efficient Very high speed integrated circuit Hardware Description Language (VHDL) code, increasing productivity by reducing the design time. The optimal design, in terms of FPGA recourse occupancy, is provided using restructuring data flow graph (DFG) of control algorithm and specifying the optimal fixed-point format. The proposed approach is validated through real experiments on three-axis didactic radar platform.
暂无评论