Maryam Mirzakhani, the mother who won Fields Medal

Unbelievable and heartbreaking! Our role model since elementary school dies at 40! I still remember the days I was struggling to learn her book written for young math lovers to prepare for math Olympiad. She was ahead of us as a senior but she passed all the elevation steps very fast, and soon she became […]

Skeleton Matching for Severe Weather Detection

Title: Skeleton Matching with Applications in Severe Weather Detection Authors: Mohammad Mahdi Kamani, Farshid Farhat, Stephen Wistar and James Z. Wang. Elsevier Journal: Applied Soft Computing, ~27 pages, May 2017. Abstract: Severe weather conditions cause an enormous amount of damages around the globe. Bow echo patterns in radar images are associated with a number of […]

Shape matching for automated bow echo detection

Abstract: Severe weather conditions cause enormous amount of damages around the globe. Bow echo patterns in radar images are associated with a number of these destructive thunderstorm conditions such as damaging winds, hail and tornadoes. They are detected manually by meteorologists. In this paper, we propose an automatic framework to detect these patterns with high […]

Stochastic Modeling and Optimization of Stragglers

Abstract: MapReduce framework is widely used to parallelize batch jobs since it exploits a high degree of multi-tasking to process them. However, it has been observed that when the number of servers increases, the map phase can take much longer than expected. This paper analytically shows that the stochastic behavior of the servers has a […]

Optimal Scheduling in Parallel Programming Frameworks

FORK-JOIN QUEUE MODELING AND OPTIMAL SCHEDULING IN PARALLEL PROGRAMMING FRAMEWORKS ABSTRACT MapReduce framework is widely used to parallelize batch jobs since it exploits a high degree of multi-tasking to process them. However, it has been observed that when the number of servers increases, the map phase can take much longer than expected. This thesis analytically […]

Towards Stochastically Optimizing Data Computing Flows

Abstract: With rapid growth in the amount of unstructured data produced by memory-intensive applications, large scale data analytics has recently attracted increasing interest. Processing, managing and analyzing this huge amount of data poses several challenges in cloud and data center computing domain. Especially, conventional frameworks for distributed data analytics are based on the assumption of […]

Stochastic Optimization of Stragglers in MapReduce

Abstract: MapReduce framework is widely used to parallelize batch jobs since it exploits a high degree of multi-tasking to process them. However, it has been observed that when the number of servers increases, the map phase can take much longer than expected. This thesis analytically shows that the stochastic behavior of the servers has a […]

Blind detection of low-rate embedding

Abstract: Steganalysis of least significant bit (LSB) embedded images in spatial domain has been investigated extensively over the past decade and most well-known LSB steganography methods have been shown to be detectable. However, according to the latest findings in the area, two major issues of very low-rate (VLR) embedding and content-adaptive steganography have remained hard […]

Modeling and Optimization of Straggling Mappers

ABSTRACT MapReduce framework is widely used to parallelize batch jobs since it exploits a high degree of multi-tasking to process them. However, it has been observed that when the number of mappers increases, the map phase can take much longer than expected. This paper analytically shows that stochastic behavior of mapper nodes has a negative […]

Image Steganalysis of Low Rate Embedding in Spatial Domain

Abstract LSB embedding in spatial domain with very low rate can be easily performed and its detection in spite of many researches is very hard, while BOSS competition has been held to break an adaptive embedding algorithm with low rate. Thus, proposing powerful steganalyzer of very low rate in spatial domain is highly requested. In […]