Weirdo, No. 18

28 volumes : illustrations. Frequency: quarterly. Publication dates: No. 1 (spring, 1981), ceased with no. 28 (summer, 1993). Editor: R. Crumb. With issue #10, P. Bagge became editor; with issue #18, Crumb\u27s wife, Aline Kominsky-Crumb became editor (except for issue #25, which was again edited by Bagge).Color illustrations on covers, b&w interiors. Early issues of Weirdo reflect Crumb\u27s interests at the time outsider art, fumetti, Church of the SubGenius-type anti-propaganda and assorted weirdness. It also introduced artists such as Peter Bagge, Dori Seda and Dennis Worden. No. 18 Contributors: Robert Crumb, Diane Noomin, Peter Bagge, Justin Green, Michael Dougan, Aline Kominsky-Crumb, Dori Seda, Spain Rodriguez, Linda Crothers, Carol Tyler, and more. Library has two copies of no. 27. The Adler Archive of Underground Comix, Gift of Bill Adler.https://digitalcommons.risd.edu/specialcollections_adlerarchive_undergroundcomix/1117/thumbnail.jp

The SEArch smart environments architecture

we report on a Smart Environment Architecture (SEArch) which has been developed to support innovative Ambient Assisted Living services. We explain SEArch at a conceptual level and also how it has been linked to a sensing environment. We compare SEArch to other similar systems reported in the technical literature. We illustrate how the system works using a practical automation scenario

Modeling auxin feedback signaling for polarized auxin transport in plant development

Plants are fascinating biological systems with a great potential for adaption of their developmental programs to environmental cues. In contrast to animals, plants cannot run away and thus they had to develop specialized mechanisms to react to rapid changes in the environment. These plant-specific mechanisms including light perception, tropism and developmental reprogramming (de novo organ formation, tissue re-shaping), represent highly dynamic regulatory processes that are linked and intertwined on the molecular, cellular and tissue levels. The ultimate communication between these different levels is the key to understand how plants realize their developmental decisions. Cell signaling, tissue polarization, directional transport of signaling molecules within tissues are among those biological processes that allow for such multilevel organization in plant development. Nevertheless our understanding of these processes remains largely elusive. This doctoral thesis demonstrates the results of multidisciplinary studies at the interface between several scientific disciplines, including mathematics, computer science (under supervision of Prof. Willy Govaerts) and cell and developmental biology (under guidance of Prof. Jiří Friml). Therefore, I will utilize state-of-the-art mathematical and computational techniques combined with the most recent biological data to address cell and tissue polarities as well as graded distribution patterns of the plant phytohormone auxin, in the context of plant developmental flexibility. The main goal of the research presented herein was to explore general principles of auxin feedback regulation and its outstanding roles in auxin-driven plant development. A special focus was given to the combination of local auxin signaling cues (inside and outside of the cell), subcellular dynamics (trafficking of auxin carriers) and cell-type specific factors (spatial patterns of gene activity) to account for the developmental patterns observed in planta such as canalization of auxin transport, leaf venation patterning, tissue regeneration and establishment and maintenance of cell and tissue polarities. The core of the thesis will start with a general introduction to the models for auxin-mediated plant development and will be followed by presentation of various scientific results and their potential implications for hopefully better understanding of patterning mechanisms in plants. Finally, the summarizing chapter of this thesis aims to translate the results of these various studies to the more general concept of the local auxin feedback regulation in plants

my Human Brain Project (mHBP)

How can we make an agent that thinks like us humans? An agent that can have proprioception, intrinsic motivation, identify deception, use small amounts of energy, transfer knowledge between tasks and evolve? This is the problem that this thesis is focusing on. Being able to create a piece of software that can perform tasks like a human being, is a goal that, if achieved, will allow us to extend our own capabilities to a very high level, and have more tasks performed in a predictable fashion. This is one of the motivations for this thesis. To address this problem, we have proposed a modular architecture for Reinforcement Learning computation and developed an implementation to have this architecture exercised. This software, that we call mHBP, is created in Python using Webots as an environment for the agent, and Neo4J, a graph database, as memory. mHBP takes the sensory data or other inputs, and produces, based on the body parts / tools that the agent has available, an output consisting of actions to perform. This thesis involves experimental design with several iterations, exploring a theoretical approach to RL based on graph databases. We conclude, with our work in this thesis, that it is possible to represent episodic data in a graph, and is also possible to interconnect Webots, Python and Neo4J to support a stable architecture for Reinforcement Learning. In this work we also find a way to search for policies using the Neo4J querying language: Cypher. Another key conclusion of this work is that state representation needs to have further research to find a state definition that enables policy search to produce more useful policies. The article “REINFORCEMENT LEARNING: A LITERATURE REVIEW (2020)” at Research Gate with doi 10.13140/RG.2.2.30323.76327 is an outcome of this thesis.Como podemos criar um agente que pense como nós humanos? Um agente que tenha propriocepção, motivação intrínseca, seja capaz de identificar ilusão, usar pequenas quantidades de energia, transferir conhecimento entre tarefas e evoluir? Este é o problema em que se foca esta tese. Ser capaz de criar uma peça de software que desempenhe tarefas como um ser humano é um objectivo que, se conseguido, nos permitirá estender as nossas capacidades a um nível muito alto, e conseguir realizar mais tarefas de uma forma previsível. Esta é uma das motivações desta tese. Para endereçar este problema, propomos uma arquitectura modular para computação de aprendizagem por reforço e desenvolvemos uma implementação para exercitar esta arquitetura. Este software, ao qual chamamos mHBP, foi criado em Python usando o Webots como um ambiente para o agente, e o Neo4J, uma base de dados de grafos, como memória. O mHBP recebe dados sensoriais ou outros inputs, e produz, baseado nas partes do corpo / ferramentas que o agente tem disponíveis, um output que consiste em ações a desempenhar. Uma boa parte desta tese envolve desenho experimental com diversas iterações, explorando uma abordagem teórica assente em bases de dados de grafos. Concluímos, com o trabalho nesta tese, que é possível representar episódios em um grafo, e que é, também, possível interligar o Webots, com o Python e o Neo4J para suportar uma arquitetura estável para a aprendizagem por reforço. Neste trabalho, também, encontramos uma forma de procurar políticas usando a linguagem de pesquisa do Neo4J: Cypher. Outra conclusão chave deste trabalho é que a representação de estados necessita de mais investigação para encontrar uma definição de estado que permita à pesquisa de políticas produzir políticas que sejam mais úteis. O artigo “REINFORCEMENT LEARNING: A LITERATURE REVIEW (2020)” no Research Gate com o doi 10.13140/RG.2.2.30323.76327 é um sub-produto desta tese

ODESeW. Automatic Generation of Knowledge Portals for Intranets and Extranets

This paper presents ODESeW (Semantic Web Portal based on WebODE platform [1]) as an ontology-based application that automatically generates and manages a knowledge portal for Intranets and Extranets. ODESeW is designed on the top of WebODE ontology engineering platform. This paper shows the service architecture that allows configuring the visualization of ontology-based information for different kinds of users, establishing reading and updating access policies to its content, and performing consistency checking between the portal information and the ontologies underlying it

Innovator, 1980-05-20

The Innovator was a student newspaper published at Governors State University between March 1972 and October 2000. The newspaper featured student reporting, opinions, news, photos, poetry, and original graphics

ONLY PROBLEMS, NOT SOLUTIONS!

The development of mathematics continues in a rapid rhythm, some unsolved problems are elucidated and simultaneously new open problems to be solved appear

Photonic-Doppler-Velocimetry, Paraxial-Scalar Diffraction Theory and Simulation

Author Institution: Lawrence Livermore National Laborator