Finding Significant Fourier Coefficients: Clarifications, Simplifications, Applications and Limitations

Ideas from Fourier analysis have been used in cryptography for the last three decades. Akavia, Goldwasser and Safra unified some of these ideas to give a complete algorithm that finds significant Fourier coefficients of functions on any finite abelian group. Their algorithm stimulated a lot of interest in the cryptography community, especially in the context of `bit security'. This manuscript attempts to be a friendly and comprehensive guide to the tools and results in this field. The intended readership is cryptographers who have heard about these tools and seek an understanding of their mechanics and their usefulness and limitations. A compact overview of the algorithm is presented with emphasis on the ideas behind it. We show how these ideas can be extended to a `modulus-switching' variant of the algorithm. We survey some applications of this algorithm, and explain that several results should be taken in the right context. In particular, we point out that some of the most important bit security problems are still open. Our original contributions include: a discussion of the limitations on the usefulness of these tools; an answer to an open question about the modular inversion hidden number problem

Impact of the Pandemic on Occupational Employment by Race

This article examines the impact of the pandemic on occupational employment by race and ethnicity. United States federal EEO laws related to race led to increased labor force diversity prior to the pandemic. Still, they did not prevent differential outcomes during the pandemic. Previous research examined total employment by race during the pandemic, and this research extends that body of knowledge by examining post-pandemic outcomes and analyzing the extent to which occupational segregation impacted employment outcomes. The data indicate that occupational segregation did not cause the pandemic related rate of employment declines by race. Specifically, Black and Asian workers had the highest rates of layoffs compared to White and Hispanic workers. However, Black workers were heavily represented in high-layoff occupations, and Asian workers in low-layoff occupations

Testing an integrated destination image model across residents and tourists

Tourism research has yet to confirm whether an integrated destination image model is applicable in predicting the overall destination image and behavioral intentions of local residents. This study examines whether the cognitive, affective and overall image - hypothesized to be predictors of behavioral intentions - are applicable to residents and tourists in the resort city of Eilat. The proposed model allowed for the distinct effect of each image component on overall image and behavior to be closely examined. The findings support the applicability of the model to local residents and also showed that among tourists, the affective component exerted a greater influence than the cognitive on overall destination image and future behavior. These findings have theoretical and practical implications for research on destination image

Understanding the experiences of asylum seekers

Purpose – The purpose of this paper is to highlight the key issues of concern for asylum seekers in the UK by focusing on their in depth talk about their experiences, a so far neglected element in the current debate about asylum seeking. Design/methodology/approach – The study involved thematic analysis of asylum seekers’ accounts of their lives in their country of origin, their journeys to the UK and experiences following arrival. Nine participants took part in semi-structured interviews. Findings – Analysis resulted in seven themes; the importance of safety, negative experiences of the Home Office, support, emotional effects, significance of family, hopes for the future and the positive experiences of living in the UK. Research limitations/implications – Asylum seekers largely left their countries of origin to escape conflict, persecution, violence, arranged marriages and rape. They reported safety as a key concern and for this reason they were scared to return home. Practical implications – The research found Asylum seekers have fled traumatic situations and then have a difficult time in the UK. A more compassionate and supportive approach is needed. Policy recommendations are made with the aim of improving service responses. Social implications – The research demonstrates that the public understanding of asylum seeking does not match asylum seekers’ experiences and increased knowledge may help to improve this (mis) understanding. Originality/value – There is currently a lack of literature and empirical investigation of this subject area, so this research makes a contribution to the field of understanding asylum seekers’ experiences. The paper's focus is original and important combining asylum seekers’ accounts of their experiences following arrival in the UK. This subject is strategically important due to the pressing need to develop holistic and culturally sensitive research, which bridges and informs academia, more sensitive service responses and civil society

Neural Attentive Session-based Recommendation

Given e-commerce scenarios that user profiles are invisible, session-based recommendation is proposed to generate recommendation results from short sessions. Previous work only considers the user's sequential behavior in the current session, whereas the user's main purpose in the current session is not emphasized. In this paper, we propose a novel neural networks framework, i.e., Neural Attentive Recommendation Machine (NARM), to tackle this problem. Specifically, we explore a hybrid encoder with an attention mechanism to model the user's sequential behavior and capture the user's main purpose in the current session, which are combined as a unified session representation later. We then compute the recommendation scores for each candidate item with a bi-linear matching scheme based on this unified session representation. We train NARM by jointly learning the item and session representations as well as their matchings. We carried out extensive experiments on two benchmark datasets. Our experimental results show that NARM outperforms state-of-the-art baselines on both datasets. Furthermore, we also find that NARM achieves a significant improvement on long sessions, which demonstrates its advantages in modeling the user's sequential behavior and main purpose simultaneously.Comment: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. arXiv admin note: text overlap with arXiv:1511.06939, arXiv:1606.08117 by other author

Effects of Noise on Galaxy Isophotes

The study of shapes of the images of objects is an important issue not only because it reveals its dynamical state but also it helps to understand the object's evolutionary history. We discuss a new technique in cosmological image analysis which is based on a set of non-parametric shape descriptors known as the Minkowski Functionals (MFs). These functionals are extremely versatile and under some conditions give a complete description of the geometrical properties of objects. We believe that MFs could be a useful tool to extract information about the shapes of galaxies, clusters of galaxies and superclusters. The information revealed by MFs can be utilized along with the knowledge obtained from currently popular methods and thus could improve our understanding of the true shapes of cosmological objects.Comment: 3 pages, 1 figure, to appear in "The IGM/Galaxy Connection - The Distribution of Baryons at z=0" Conference Proceeding

Boston Hospitality Review: Spring 2016

Understanding the Momentum and Motivations of Foreign Investors in U.S. Hospitality by Ken Wilson and Liya Ma -- Creating Memorable Experiences: How hotels can fight back against Airbnb and other sharing economy providers by Makarand Mody -- Rebranding Before the Digital Age: 4 Strategies Used by the Sheraton New York Hotel and Towers During the 1992 Democratic National Convention by Leora Halpern Lanz, Juan Lesmes, and Erinn Tucker -- Federal Minimum Wage Debate: Are Gubernatorial Politics Behind a Hotel Line Employee Wage? by Nicholas Thomas and Eric Brown -- Rethinking Substance Use and Abuse Among Hospitality Employees by Amir Shani -- Consumers’ Desires in Hostels: Addressing Latent and Explicit Needs in United States Hostels by Emily Horto

The Multivariate Hidden Number Problem

This work extends the line of research on the hidden number problem. Motivated by studying bit security in finite fields, we define the multivariate hidden number problem. Here, the secret and the multiplier are vectors, and partial information about their dot product is given. Using tools from discrete Fourier analysis introduced by Akavia, Goldwasser and Safra, we show that if one can find the significant Fourier coefficients of some function, then one can solve the multivariate hidden number problem for that function. This allows us to generalise the work of Akavia on the hidden number problem with (non-adaptive) chosen multipliers to all finite fields. We give two further applications of our results, both of which generalise previous works to all (finite) extension fields. The first considers the general (random samples) hidden number problem in F_{p^m} and assumes an advice is given to the algorithm. The second considers a model that allows changing representations, where we show hardness of individual bits for elliptic curve and pairing based functions for elliptic curves over extension fields, as well as hardness of any bit of any component of the Diffie-Hellman secret in F_{p^m} (m>1)