Public-key cryptography is a fundamental component of modern electronic communication that can be constructed with many different mathematical processes. Presently, cryptosystems based on elliptic curves are becoming popular due to strong cryptographic strength per small key size. At the heart of these schemes is the intractability of the elliptic curve discrete logarithm problem (ECDLP).Pollard's Rho algorithm is a well known method for solving the ECDLP and thereby breaking ciphers based on elliptic curves. It has the same time complexity as other known methods but is advantageous due to smaller memory requirements. This paper considers how to speed up the Rho process by modifying a key component: the iterating function, which is the part of the algorithm responsible for determining what point is considered next when looking for a collision. It is replaced with an alternative that is found through an evolutionary process. This alternative consistently and significantly decreases the number of iterations required by Pollard's Rho Algorithm to successfully find a solution to the ECDLP.

Using open source hardware platforms like the Arduino, libraries have the ability to quickly and inexpensively prototype custom hardware solutions to common library problems. The authors present the Arduino environment, what it is, what it does, and how it was used at the James A. Gibson Library at Brock University to create a production portable barcode-scanning utility for in-house use statistics collection as well as a prototype for a service desk statistics tabulation program's hardware interface.

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In February of 2016, I activated the @lis_grievances Twitter bot. The dynamics of the bot are straightforward and can be described in three steps: first, a person sends a direct message to the account; second, the message is stripped of all identifying information; and third, upon passing a minimal list of posting criteria, the message is tweeted. Five plus years on, the bot has collected a corpus of thousands of tweets, some safe to publish on Twitter and some not, ranging from benign takes on the library establishment to profanity laden tirades. Quite often, the tweets invoke feelings that range from pathos to disgust, and sometimes even situational irony and humor as evidenced, for example, in this tweet from June 1, 2018: "How can we innovate when we don't have permissions to install software?" This chapter examines tweeted content through the online disinhibition effect (ODE), a theory that attempts to explain how anonymity tends to push sentiment into more extreme directions. According to ODE, users of @lis_grievances experience a lack of restraint due to their anonymity and, thus, feel comfortable venting and otherwise offering observations of and comments on perceived flaws in their individual workplaces and in the LIS profession at large. Using text analysis and a new customized metric called the grief index, a qualitative and quantitative examination of the corpus of tweets is presented and explored as evidence of systemically dysfunctional library states.

Introduction: “Usage metrics are an effective way for libraries to demonstrate the value of their institutional repositories, however, existing tools are not always reliable and can either undercount or overcount file downloads. As well, although statistics can sometimes be accessed through the various repository interfaces, without an agreed standard it is impossible to reliably assess and compare usage data across different IRs in any meaningful way.”[1] The Task Group for Standards for IR Usage Data has undertaken an information-gathering exercise to better understand both the existing practices of Canadian repositories, as well as the emerging tools and processes available for repositories to track and monitor usage more effectively. This exercise directly links to the broader goals of the Open Repositories Working Group, which are to “strengthen and add value to the network of Canadian open access repositories by collaborating more closely and adopting a broader range of services.”[2] Our recommended course of action is for all Canadian IRs to collectively adopt OpenAIREStatistics. This path aligns with the following recommendations which our group also advances: Recommendations: We suggest the following Mandatory (M) and Optional (O) recommendations: R1(M):All Canadian IRs should adopt the COUNTER Code of Practice. R2(M): All Canadian IRs should select a service that allows for interoperability with other web services via a fully open, or accessible, permissions-based API. R3(M): All Canadian IRs should usea statistics service that practices transparent communication and maintains a governance strategy. In addition, we strongly urge for the future that Canadian IRs consider the following advice. R4(O): Make further investments into understanding and utilizing the common log format (CLF). R5(O): Conduct research into the privacy implications of collecting use statistics via third party services with commercial interests and consider available alternatives. R6(O): Practice a healthy skepticism towards tools and solutions that promise “increased” usage statistics, and instead advocate for responsible collection assessment based on multiple aspects of use.