Study Materials - (28)zip

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Study Materials - (28)zip

By the end of this course, you will have built autonomous agents that efficiently make decisions in fully informed, partially observable and adversarial settings. Your agents will draw inferences in uncertain environments and optimize actions for arbitrary reward structures. Your machine learning algorithms will classify handwritten digits and photographs. The techniques you learn in this course apply to a wide variety of artificial intelligence problems and will serve as the foundation for further study in any application area you choose to pursue.

The links below to electronic homework will only work for students who were registered in the Berkeley offering. If you are working through these materials on your own, make an account at Gradescope and enroll using this code: 93PWD8 Then onwards, this link should work:

You may wish to download your course content from Blackboard either for your records, to save for accreditation reasons, or if you leave the university. There are several ways you can download your content. See the options below for retaining access to your course materials.

Exporting your course downloads all of the course content and materials into a .zip file that can be used to import back to Blackboard at a later date. This is primarily used to keep your course if you know you or someone may want to use this in the future.

Archiving your course downloads all of the course content and materials including the grade center into a .zip file. This is primarily used to keep a record of your course. If you want to access these materials again to use in the future, we recommend that you export the course as well. It is easier to import an export of a course that it is to import an archive of a course. Archived course may not properly import.

Soldiers and leaders should be wary about utilizing EFMB study material obtained from sources other than this website. The EFMB TCO is consistently observing sites and candidates using material that is not applicable for EFMB testing. Much of the material available on other websites is outdated or irrelevant for EFMB testing purposes. BE CAREFUL WHAT YOU USE TO PREPARE! At this time we recommend utilizing the references on the "Written Test" tab to study for the EFMB written test. These materials are also available on each EFMB Written Test Blackboard site in the "References & Resources" section.

MG Duncan, Chief of Staff, US Continental Army Command recommended establishment of an Expert Field Medical Badge as a Department of the Army special skill award for recognition of exceptional competence and outstanding performance by field medical personnel in a letter to Deputy Chief of Staff for Personnel, (DCSPER), dated 20 January 1964, in accordance with correspondence between General Waters and General Heaton, The Surgeon General. (DCSPER and the Army Chief of Staff for Force Development (ACSFOR) did not favorably consider an earlier request in 1963 for the same badge.) On 14 May 1964, DCSPER tentatively approved the recommendation, subject to Headquarters US Continental Army Command and ACSFOR`s development and submission of criteria. DSCPER received the design of the badge, with criteria for the award, by Summary Sheet on 2 February 1965, and returned it without action on 27 February 1965 due to pending further study of questions posed by the Vice Chief of Staff, US Army. DCSPER advised Commander, The Institute of Heraldry (TIOH), US Army, by Disposition Form (DF), dated 6 July 1965, of the approved Summary Sheet, dated 18 June 1965, establishing an Expert Field Medical Badge. TIOH took on the responsibility of preparing the necessary Army Regulation and commencing action on procurement of the new badge. A reproduction sample of the Expert Field Medical Badge was approved on 8 December 1965. The badge was oxidized silver consisting of a stretcher placed horizontally behind a caduceus with a cross of the Geneva Convention at the junction of the wings, 15/16 inch high and 1 7/17 inches long. The badge has not changed since its inception. AR 672-10, dated 1 March 1966, prescribed the authority for the award of the badge. Current Regulations: AMEDDC&S HRCOE PAM 350-10, dated 1 March 2019.

The NIH is interested in advancing genome-wide association studies (GWAS) to identify common genetic factors that influence health and disease. For the purposes of this policy, a genome-wide association study is defined as any study of genetic variation across the entire human genome that is designed to identify genetic associations with observable traits (such as blood pressure or weight), or the presence or absence of a disease or condition. 1 Whole genome information, when combined with clinical and other phenotype data, offers the potential for increased understanding of basic biological processes affecting human health, improvement in the prediction of disease and patient care, and ultimately the realization of the promise of personalized medicine. In addition, rapid advances in understanding the patterns of human genetic variation and maturing high-throughput, cost-effective methods for genotyping are providing powerful research tools for identifying genetic variants that contribute to health and disease. For these reasons, the NIH announced in May 2006 that it planned to: (1) update NIH data sharing policies for research applications involving GWAS data; (2) initiate a public consultation process to inform policy development activities; and (3) track GWAS applications and awards at a central level (NOT-OD-06-071). A call for public comments on a proposed GWAS policy was issued on August 30, 2006 (NOT-OD-06-094). Between August 30 and November 30, 2006, the NIH solicited public comments from a range of public sectors (see Preamble below). Following the comment period, NIH convened a Town Hall Meeting in Bethesda, Maryland on December 14, 2006, to provide an opportunity for direct interaction with interested stakeholders on the important policy questions raised through the proposed policy (NOT-OD-07-022). This Notice provides the NIH response to the public comments received during the public consultation activities and presents the revised GWAS policy developed by the NIH in response to the feedback received and further internal development of the issues. The policy addresses (1) data sharing procedures, (2) data access principles, (3) intellectual property, and (4) issues regarding the protection of research participants through all phases of GWAS. Many of the principles contained in the policy reflect existing NIH polices and other NIH discussions. The goal of the policy is to advance science for the benefit of the public through the creation of a centralized NIH GWAS data repository 2. Maximizing the availability of resources facilitates research and enables medical science to better address the health needs of people based on their individual genetic information.Protecting Research Participants

Respondents asked for clarification of plans for return of results to study participants. The NIH does not anticipate that participants will be able to obtain individual results of secondary analyses on data obtained from their participation in primary studies. Because the NIH GWAS data repository and secondary data users will not have access to identifying information or to the link to the keycode within the data, neither will be able to return individual results directly to subjects. Secondary investigators may share their findings with primary investigators, who may determine whether it is appropriate to return individual or aggregate research results to participants whose health may be affected, following established institutional procedures (e.g., IRB approval) and specific parameters defined within the original study.

The NIH is interested in advancing genome-wide association studies (GWAS) to identify common genetic factors that influence health and disease. For the purposes of this policy, a genome-wide association study is defined as any study of genetic variation across the entire human genome that is designed to identify genetic associations with observable traits (such as blood pressure or weight), or the presence or absence of a disease or condition 1. Whole genome information, when combined with clinical and other phenotype data, offers the potential for increased understanding of basic biological processes affecting human health, improvement in the prediction of disease and patient care, and ultimately the realization of the promise of personalized medicine. In addition, rapid advances in understanding the patterns of human genetic variation and maturing high-throughput, cost-effective methods for genotyping are providing powerful research tools for identifying genetic variants that contribute to health and disease. Consistent with the NIH mission to improve public health through research, the NIH believes that the full value of GWAS to the public can be realized only if the genotype and phenotype datasets are made available as rapidly as possible to a wide range of scientific investigators. Rapid and broad data access is particularly important for GWAS because of the significant resources they require; the challenges of analyzing large datasets; and the extraordinary opportunities for making comparisons across multiple studies. Protection of research participants is a fundamental principle underlying biomedical research. The NIH is committed to responsible stewardship of data throughout the research process, which is essential to protecting the interests of study participants and to maintaining public trust in biomedical research. In consideration of the evolving scientific, ethical, and societal issues related to this policy, the NIH is establishing a governance structure for NIH GWAS activities that will: 041b061a72