SON-POWERED DYNAMIC OPTIMIZATION OF RELAY LAYER TO ENHANCE COVERAGE AND CAPACITY OF A CELLULAR NETWORK COMBINED WITH CENTRALIZED SON ON MACRO LAYER

The usage patterns of cellular networks can change dramatically over short periods of time, such as when a large number of people crowd a very small space within a cell\u27s coverage area for only a short period of time. In order to save on costly and inefficient current solutions, the techniques presented herein suggest a Self-Organizing Network (SON)-optimized system of relays as a layer on top of an existing system. Such relays can be deployed ad hoc, such as in the cars of people arriving at a troubled location, to alleviate temporary coverage and load issues. SON will control the activation and deactivation of these ad hoc relays and the joint optimization of both the macro and relay layers

Online answers dealing with the internment of Japanese-Americans during World War II

The internment of Americans of Japanese descent during World War II lies at the heart of ongoing discussions in American social studies. We analyzed inputs of members of the Yahoo! Answers Q&A online community following students’ questions dealing with differential treatment of Japanese, and German and Italian American citizens during World War II, and whether the internment of Japanese Americans was justified. The questions were submitted to the community by students struggling with their coursework. The majority of responses to first question justified the differential treatment, citing national security and presenting Japanese-Americans as a threat. The dominant position in the case of the second question negates internment legitimacy, and views it as a gross violation of justice and as a racially motivated act. These stances, likely to make their way into submitted assignments by students, necessitate the familiarization of teachers with such discussions as they take place within Q&A communities

The power of negations in cryptography

The study of monotonicity and negation complexity for Bool-ean functions has been prevalent in complexity theory as well as in computational learning theory, but little attention has been given to it in the cryptographic context. Recently, Goldreich and Izsak (2012) have initiated a study of whether cryptographic primitives can be monotone, and showed that one-way functions can be monotone (assuming they exist), but a pseudorandom generator cannot. In this paper, we start by filling in the picture and proving that many other basic cryptographic primitives cannot be monotone. We then initiate a quantitative study of the power of negations, asking how many negations are required. We provide several lower bounds, some of them tight, for various cryptographic primitives and building blocks including one-way permutations, pseudorandom functions, small-bias generators, hard-core predicates, error-correcting codes, and randomness extractors. Among our results, we highlight the following. Unlike one-way functions, one-way permutations cannot be monotone. We prove that pseudorandom functions require logn − O(1) negations (which is optimal up to the additive term). We prove that error-correcting codes with optimal distance parameters require logn − O(1) negations (again, optimal up to the additive term). We prove a general result for monotone functions, showing a lower bound on the depth of any circuit with t negations on the bottom that computes a monotone function f in terms of the monotone circuit depth of f. This result addresses a question posed by Koroth and Sarma (2014) in the context of the circuit complexity of the Clique problem

Bayesian Analysis of Linear Contracts

We provide a justification for the prevalence of linear (commission-based) contracts in practice under the Bayesian framework. We consider a hidden-action principal-agent model, in which actions require different amounts of effort, and the agent's cost per-unit-of-effort is private. We show that linear contracts are near-optimal whenever there is sufficient uncertainty in the principal-agent setting