Semantic Scholar Information is Unreliable and FALSE!

The website is spreading wrong info about many scholars, their papers and their citations. Just try my name: www.semanticscholar.org/search?q=farshid%20farhat&sort=relevance www.semanticscholar.org/author/Farshid-Farhat/2052042 It was better to supervise/verify the info before making public on the web, otherwise shut it down! I’m totally disappointed with SemanticScholar!  

Auction-based Resource Management in Computer Architecture

ABSTRACT Resource management systems rely on a centralized approach to manage applications running on each resource. The centralized resource management system is not efficient and scalable for large-scale servers as the number of applications running on shared resources is increasing dramatically and the centralized manager may not have enough information about applications’ need. This work […]

Split AT&T Bill in a Shared Data Plan

Getting fair shares for a shared data plan is always disaster! Because it is not a simple +/- but also there are a lot of overheads included inside the charges such as tax and extras, and also AT&T doesn’t divide the data charge and overage among the lines but only one line! The attached EXCEL […]

Collaborators

Graduates: Diman Zad Tootaghaj Danial M.M. Kamani Yu Luo Undergrads: Sahil Mishra Luke Porupski Jeremy Ong Yizhi Huang Jeffery Cao Shengguang Bai

Publications

Discovering Triangles in Portraits for Supporting Photographic Creation, S He, Z Zhou, F Farhat, JZ Wang, IEEE Transactions on Multimedia, Aug 2017. Intelligent Portrait Composition Assistance — Integrating Deep-learned Models and Photography Idea Retrieval, F Farhat, MM Kamani, S Mishra, JZ Wang, July 2017. Skeleton Matching with Applications in Severe Weather Detection, MM Kamani, F […]

Leveraging big visual data to predict severe weather

NEWS SOURCEs [www.sciencedaily.com/releases/2017/06/170621145133.htm www.eurekalert.org/pub_releases/2017-06/ps-nir062117.php phys.org/news/2017-06-leverages-big-severe-weather.html sciencenewsline.com/news/2017062217300053.html] Every year, severe weather endangers millions of people and causes billions of dollars in damage worldwide. But new research from Penn State’s College of Information Sciences and Technology (IST) and AccuWeather has found a way to better predict some of these threats by harnessing the power of big data. […]

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 […]

Thumbnail Generation by Smart Cropping

Given any aspect ratio, oval shape, or automatically AutoThumbGen generates a thumbnail based on the input image. In fact, the most prominent part of the input image is recognized and captured by the app with a proper thumbnail size. The source code is in C. The code has been also embedded in Android via JNI and PHP by […]

Big Data Computing: Modeling and Optimization

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 […]