Kinetic surface roughening for the Mullins-Herring equation

Using the linearity property of the Mullins-Herring equation when the velocity is zero with a Gaussian noise, we obtain an analytic form for the global mean-square surface width and height-height correlation function. This can be used to read the critical exponents in any dimension. In particular for d=1 we show that although the surface is super rough the system exhibits Family-Vicsek scaling behavior.Comment: 5 page

Diffusion of Latent Semantic Analysis as a Research Tool: A Social Network Analysis Approach

Latent Semantic Analysis (LSA) is a relatively new research tool with a wide range of applications in different fields ranging from discourse analysis to cognitive science, from information retrieval to machine learning and so on. In this paper, we chart the development and diffusion of LSA as a research tool using Social Network Analysis (SNA) approach that reveals the social structure of a discipline in terms of collaboration among scientists. Using Thomson Reuters’ Web of Science (WoS), we identified 65 papers with “Latent Semantic Analysis” in their titles and 250 papers in their topics (but not in titles) between 1990 and 2008. We then analyzed those papers using bibliometric and SNA techniques such as co-authorship and cluster analysis. It appears that as the emphasis moves from the research tool (LSA) itself to its applications in different fields, citations to papers with LSA in their titles tend to decrease. The productivity of authors fits Lotka’s Law while the network of authors is quite loose. Networks of journals cited in papers with LSA in their titles and topics are well connected

THE IMPACT OF AUTHENTIC LEADERSHIP ON JOB SATISFACTION AND TEAM COMMITMENT

One of the challenges toward organization is maintaining good employees in competitive business environment in order to achieve their goals. Employees’ feeling and attitude to their job, team and organization is an important factor which can’t be ignored by organization. In other words, the employees’ effective response to different aspect of job and organization will have several effects on their performance and behavior. One of the important factors in all organizations is organizational leadership as one of the most key strategies to achieving this purpose. Authentic leadership as one of the areas raised in the literature of modern leadership in recent years has been considered by researchers and practitioners. In this study, we explored the impact of authentic leadership and its elements on team commitment and job satisfaction. 80 questionnaires were filled by employees and analyzed by SPSS 18.0 software. According to obtained results, there were meaningful and positive correlation between authentic leadership, job satisfaction and team commitment. Also we conclude that teams with more authentic characteristics in their leaders, had more satisfied and committed employees.authentic leadership, balanced processing, job satisfaction, moral/ethics, self awareness, team commitment, transparency.

DeepMarks: A Digital Fingerprinting Framework for Deep Neural Networks

This paper proposes DeepMarks, a novel end-to-end framework for systematic fingerprinting in the context of Deep Learning (DL). Remarkable progress has been made in the area of deep learning. Sharing the trained DL models has become a trend that is ubiquitous in various fields ranging from biomedical diagnosis to stock prediction. As the availability and popularity of pre-trained models are increasing, it is critical to protect the Intellectual Property (IP) of the model owner. DeepMarks introduces the first fingerprinting methodology that enables the model owner to embed unique fingerprints within the parameters (weights) of her model and later identify undesired usages of her distributed models. The proposed framework embeds the fingerprints in the Probability Density Function (pdf) of trainable weights by leveraging the extra capacity available in contemporary DL models. DeepMarks is robust against fingerprints collusion as well as network transformation attacks, including model compression and model fine-tuning. Extensive proof-of-concept evaluations on MNIST and CIFAR10 datasets, as well as a wide variety of deep neural networks architectures such as Wide Residual Networks (WRNs) and Convolutional Neural Networks (CNNs), corroborate the effectiveness and robustness of DeepMarks framework