Unread Letters to My Mother

The poem Unread Letters to My Mother is a meditation on dream and memory and how PTSD brought on by childhood trauma has effected those things within the speaker\u27s life. Each of the seven sections are addressed to the speaker\u27s mother, but the reader knows these are things which are left unsaid, in the darkness, as the clarity and insight they provide into the speaker\u27s life is perhaps too overwhelming for the figure of the mother to process

The Empath’s Travel Log

Cynthia Marie Hoffman Studner said of the poem, This is an ambitious poem that delivers on empathy, just as promised. The poem establishes a metaphor of a “taught thread” that pulls together the traveler and an “orange-coated mutt” spotted in Italy, and this thread weaves throughout the poem as one of continual and deep connection with others. One wonders of the empath’s fate, especially when the poem begins with the story of wives cremated beside their dead husbands. What are the implications of this empathy in terms of its being something the speaker must bear? At times, it is guilt, as in the case of the baby rabbit that cannot be saved. Later, it is the insensitivity of a father who laughs and orders a rabbit cooked and delivered on a plate. It seems the speaker ultimately comes to find purpose and usefulness in empathy, saving animals after all (making the dream come true in which “the thread connecting/ me to you does not snap,/ and you live,/ and you live”). But it is the stark absence of animals and others in the final section that haunts me. The tension and strangeness in the ending lines is satisfying in a way that resists closure. I want more, but at the same time, I don’t want more. And that seems just right

State Welfare-to-Work Policies for People with Disabilities

This study represents a first attempt to provide a nationwide overview of welfare-to-work policies for individuals with disabilities and caregivers. The major findings of this report are: (c) The majority of states have changed their work participation policies to require participation among some individuals with disabilities and caregivers who were previously exempt. (c) States are in the early stages of making decisions about who should be required to participate in welfare-to-work services, who should be expected to move off welfare within 60 months, and what services will best help recipients achieve this objective

Populations of models, Experimental Designs and coverage of parameter space by Latin Hypercube and Orthogonal Sampling

In this paper we have used simulations to make a conjecture about the coverage of a $t$ dimensional subspace of a $d$ dimensional parameter space of size $n$ when performing $k$ trials of Latin Hypercube sampling. This takes the form $P(k,n,d,t)=1-e^{-k/n^{t-1}}$. We suggest that this coverage formula is independent of $d$ and this allows us to make connections between building Populations of Models and Experimental Designs. We also show that Orthogonal sampling is superior to Latin Hypercube sampling in terms of allowing a more uniform coverage of the $t$ dimensional subspace at the sub-block size level.Comment: 9 pages, 5 figure

Efficiently Learning Monotone Decision Trees with ID3

Since the Probably Approximately Correct learning model was introduced in 1984, there has been much effort in designing computationally efficient algorithms for learning Boolean functions from random examples drawn from a uniform distribution. In this paper, I take the ID3 information-gain-first classification algorithm and apply it to the task of learning monotone Boolean functions from examples that are uniformly distributed over {0,1}^n. I limited my scope to the class of monotone Boolean functions that can be represented as read-2 width-2 disjunctive normal form expressions. I modeled these functions as graphs and examined each type of connected component contained in these models, i.e. path graphs and cycle graphs. I determined the influence of the variables in the pieces of these graph models in order to understand how ID3 behaves when learning these functions. My findings show that ID3 will produce an optimal decision tree for this class of Boolean functions