Camera-Based Ballot Counter

Portable ballot counters using camera technology and manual paper feed are potentially more reliable and less expensive than scanner based systems. We show that the spatial sampling rate, geometric linearity, point spread function, and photometric transfer function of off-the-shelf consumer cameras are acceptable for ballot imaging. However, scanner illumination is much more uniform than can be economically accomplished for variable size ballots. Therefore flat-field compensation must be designed into the image processing software. We illustrate the mechanical design of a prototype camera based ballot reader based on our comparative observations

Combatting electoral traces: the Dutch tempest discussion and beyond

In the Dutch e-voting debate, the crucial issue leading to the abandonment of all electronic voting machines was compromising radiation, or tempest. Other countries, however, do not seem to be bothered by this risk. In this paper, we use actor-network theory to analyse the socio-technical origins of the Dutch tempest issue in e-voting, and its consequences for e-voting beyond the Netherlands. We introduce the term electoral traces to denote any physical, digital or social evidence of a voter's choices in an election. From this perspective, we provide guidelines for risk analysis as well as an overview of countermeasures

2016 Correspondence from Leonard Scott to Cheryl Beredo explaining the Sioux Products, Inc. v. NLRB Case Decided by the U.S. Court of Appeals, Seventh Circuit, on March 24, 1983.

A letter and photocopies of the Explanation of the Sioux Products, Inc.v. NLRB. 703 Federal Reporter, 2d Series. pp. 1010- 1019

"Too close to call" : CNN's politics of captions in the coverage of the Florida Recount

Proceeding chronologically in terms of the events covered, Raimund Schieß in his paper „Too close to call: CNN’s politics of captions in the coverage of the Florida Recount“ focusses on Nov. 11, 2000, when the Bush campaign applied to Miami Federal Court to stop the manual recount of ballots which had been started in some counties. The paper studies the discursive practices employed by the CNN journalists to construct a particular version of the events, focussing on captions, i.e. the lines of text inserted at the bottom of the tv screen, and on the way in which they interact with the other verbal and visual components of the television text. Raimund Schieß concludes that captions, far beyond providing mere details of a speech event (who is talking to whom about what, where and when), are used to select, to highlight and hide, and thus to invite a preferred interpretation of the event. He is also able to show that captions are often employed to exploit a story’s potential for drama and sensation. His detailed micro-analysis of the verbal and visual dimensions of the television text is supported by careful documentation of the data, either through screen shots or via transcriptions of the stretches of broadcast discussed

HandiVote: simple, anonymous, and auditable electronic voting

We suggest a set of procedures utilising a range of technologies by which a major democratic deficit of modern society can be addressed. The mechanism, whilst it makes limited use of cryptographic techniques in the background, is based around objects and procedures with which voters are currently familiar. We believe that this holds considerable potential for the extension of democratic participation and control

The Cowl - v.16 - n.2 - Sep 30, 1953

The Cowl - student newspaper of Providence College. Volume 16, Number 2 - Sep 30, 1953, 1951. 6 pages

Spartan Daily, May 7, 2004

Volume 122, Issue 63https://scholarworks.sjsu.edu/spartandaily/9997/thumbnail.jp

Time-Domain Data Fusion Using Weighted Evidence and Dempster–Shafer Combination Rule: Application in Object Classification

To apply data fusion in time-domain based on Dempster–Shafer (DS) combination rule, an 8-step algorithm with novel entropy function is proposed. The 8-step algorithm is applied to time-domain to achieve the sequential combination of time-domain data. Simulation results showed that this method is successful in capturing the changes (dynamic behavior) in time-domain object classification. This method also showed better anti-disturbing ability and transition property compared to other methods available in the literature. As an example, a convolution neural network (CNN) is trained to classify three different types of weeds. Precision and recall from confusion matrix of the CNN are used to update basic probability assignment (BPA) which captures the classification uncertainty. Real data of classified weeds from a single sensor is used test time-domain data fusion. The proposed method is successful in filtering noise (reduce sudden changes—smoother curves) and fusing conflicting information from the video feed. Performance of the algorithm can be adjusted between robustness and fast-response using a tuning parameter which is number of time-steps(ts)