Parsing the stream of time: The value of event-based segmentation in a complex real-world control problem

1998 ◽  
pp. 370-388 ◽  
Author(s):  
Michael C. Mozer ◽  
Debra Miller
Keyword(s):  
Control Problem ◽  
Real World ◽  
Event Based

scholarly journals Debugging Nondeterministic Failures in Linux Programs through Replay Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Shakaiba Majeed ◽  
Minsoo Ryu
Keyword(s):  
Real World ◽  
Production Systems ◽  
Memory Access ◽  
Analysis Method ◽  
Concurrency Bugs ◽  
Real World Applications ◽  
Record And Replay ◽  
Access Patterns ◽  
Event Based ◽  
Concurrency Bug

Reproducing a failure is the first and most important step in debugging because it enables us to understand the failure and track down its source. However, many programs are susceptible to nondeterministic failures that are hard to reproduce, which makes debugging extremely difficult. We first address the reproducibility problem by proposing an OS-level replay system for a uniprocessor environment that can capture and replay nondeterministic events needed to reproduce a failure in Linux interactive and event-based programs. We then present an analysis method, called replay analysis, based on the proposed record and replay system to diagnose concurrency bugs in such programs. The replay analysis method uses a combination of static analysis, dynamic tracing during replay, and delta debugging to identify failure-inducing memory access patterns that lead to concurrency failure. The experimental results show that the presented record and replay system has low-recording overhead and hence can be safely used in production systems to catch rarely occurring bugs. We also present few concurrency bug case studies from real-world applications to prove the effectiveness of the proposed bug diagnosis framework.

scholarly journals Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks

2021 ◽  
Vol 15 (5) ◽  
pp. 1-33
Author(s):  
Hao Peng ◽  
Jianxin Li ◽  
Yangqiu Song ◽  
Renyu Yang ◽  
Rajiv Ranjan ◽  
...  
Keyword(s):  
Real Time ◽  
Real World ◽  
Event Detection ◽  
Social Event ◽  
Heterogeneous Information ◽  
Heterogeneous Information Networks ◽  
Social Events ◽  
Meta Path ◽  
Social Event Detection ◽  
Event Based

Events are happening in real world and real time, which can be planned and organized for occasions, such as social gatherings, festival celebrations, influential meetings, or sports activities. Social media platforms generate a lot of real-time text information regarding public events with different topics. However, mining social events is challenging because events typically exhibit heterogeneous texture and metadata are often ambiguous. In this article, we first design a novel event-based meta-schema to characterize the semantic relatedness of social events and then build an event-based heterogeneous information network (HIN) integrating information from external knowledge base. Second, we propose a novel Pairwise Popularity Graph Convolutional Network, named as PP-GCN, based on weighted meta-path instance similarity and textual semantic representation as inputs, to perform fine-grained social event categorization and learn the optimal weights of meta-paths in different tasks. Third, we propose a streaming social event detection and evolution discovery framework for HINs based on meta-path similarity search, historical information about meta-paths, and heterogeneous DBSCAN clustering method. Comprehensive experiments on real-world streaming social text data are conducted to compare various social event detection and evolution discovery algorithms. Experimental results demonstrate that our proposed framework outperforms other alternative social event detection and evolution discovery techniques.

Extracting Criminal-Related Events from Arabic Tweets

2017 ◽  
Vol 10 (3) ◽  
pp. 34-47
Author(s):  
Feriel Abdelkoui ◽  
Mohamed-Khireddine Kholladi
Keyword(s):  
Social Networks ◽  
Natural Hazards ◽  
Real World ◽  
Event Detection ◽  
Temporal Information ◽  
Automated Extraction ◽  
Temporal Expressions ◽  
Spatio Temporal ◽  
Event Based ◽  
F Measure

Recently, Twitter as one of social networks has been considered as a rich source of spatio-temporal information and significant revenue for mining data. Event detection from tweets can help to predict more serious real-world events. Such as: criminal events, natural hazards, and the spread of epidemics. Etc. This paper deals with event-based extraction for criminal incidents from Arabic tweets. It presents a framework that supports automated extraction of spatial and temporal information from tweets. The proposed approach is based on combining various indicators, including the names of places and temporal expressions that appear in the tweet message, related tweeting time, and additional locations from the user's profile. The effectiveness of the system was evaluated in term of recall, precision and f-measure.

scholarly journals Multipath Adaptive Tabu Search for a Vehicle Control Problem

2012 ◽  
Vol 2012 ◽  
pp. 1-20 ◽  
Author(s):  
Jukkrit Kluabwang ◽  
Deacha Puangdownreong ◽  
Sarawut Sujitjorn
Keyword(s):  
Tabu Search ◽  
Control Problem ◽  
Real World ◽  
Optimization Problems ◽  
Vehicle Control ◽  
Local Solution ◽  
Adaptive Search ◽  
Surface Optimization ◽  
Real World Problems

Tabu search has become acceptable worldwide as one of the most efficient intelligent searches applied to various real-world problems. There have been different modifications made to the generic tabu search in recent years to achieve better performances. Among those reviewed in the introduction of this paper, the adaptive tabu search (ATS) has incorporated the backtracking and the adaptive search radius mechanisms that help accelerate the search and release it from a local solution lock. The paper explains an enhancement made to the ATS to accomplish multipath ATS (MATS) algorithms. Performances of the ATS and the MATS are evaluated using surface optimization problems, and results are presented in the paper. Finally, the MATS is applied to solve a real-world vehicle control problem.

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