Sex Offender Treatment Program: Preliminary Description

This report provides a summary of the history of sex offender treatment in Alaska, including the current status of treatment programs offered by the Alaska Department of Corrections, a review of literature on sex offender treatment and recidivism issues, and a summary of the descriptive characteristics of individuals who came in contact with the Hiland Mountain Correctional Center from January 1987 to March 1993.Alaska Department of CorrectionsIntroduction / Sex Offender Treatment in Alaska / Literature Review / Methodology / Results / Conclusion and Recommendations / Bibliograph

Justice Data Base Directory

The Justice Data Base Directory was originally published in 1988 with an introduction, 8 chapters describing Alaska justice agencies and their data holdings, and an index. It was published in looseleaf notebook format for easy updating. Four updates were published in 1989–1992, each update consisting of additional chapters, revised table of contents and index, and updates to existing pages to reflect changes such as agency addresses. Five chapters were added in 1989; five in 1990; four in 1991; and five in 1992, for a total of 27 agencies covered by the Justice Data Base Directory in its final form. For archival purposes, this record includes all five versions of the directory. The 1992 edition is the most complete.The Justice Data Base Directory, first published in 1988 with new chapters added annually through 1992, presents information about the primary databases maintained by Alaska justice agencies and the procedures to be followed for access to the data. Its availability should substantially reduce the work required to identify the sources of data for research and policy development in law, law enforcement, courts, and corrections. The 1992 update to the directory adds five chapters, for a total of 27 Alaska agencies whose justice-related data holdings are described: Alaska Court System; Alaska Judicial Council; Alaska Commission on Judicial Conduct; Alaska Department of Law; Alaska Department of Public Safety (DPS) and three agencies under DPS: Alaska Police Standards Council, Council on Domestic Violence and Sexual Assault (CDSA), and Violent Crimes Compensation Board; Alaska Department of Corrections (DOC) and Parole Board; four agencies of the Alaska Department of Health and Social Services — Bureau of Vital Statistics (Division of Public Health), Epidemiology Section (Division of Public Health), Division of Family and Youth Services, and Office of Alcoholism and Drug Abuse; Alaska Public Defender Agency; Office of Public Advocacy (OPA); Alaska Bar Association; Alaska Justice Statistical Analysis Unit; Alaska Office of Equal Employment Opportunity (Office of the Governor); Alaska Office of the Ombudsman; Alaska Legal Services Corporation; Alaska Public Offices Commission; Alaska State Commission for Human Rights; Alcoholic Beverage Control (ABC) Board; Legislative Research Agency; Legislative Affairs Agency; State Archives and Records Management Services (Alaska Department of Education). Fully indexed.Funded in part by a grant from the Bureau of Justice Statistics.1. Introduction / 2. Alaska Court System / 3. Alaska Department of Law / 4. Alaska Department of Public Safety / 5. Alaska Department of Corrections / 6. Division of Family and Youth Services, Alaska Department of Health and Social Services / 7. Alaska Bar Association / 8. Alaska Judicial Council / 9. Alaska Justice Statistical Analysis Unit / 10. Bureau of Vital Statistics, Division of Public Health, Alaska Department of Health and Social Services / 11. Alaska Office of Equal Employment Opportunity, Office of the Governor / 12. Office of Alcoholism and Drug Abuse, Alaska Department of Health and Social Services / 13. Council on Domestic Violence and Sexual Assault, Alaska Department of Public Safety / 14. Epidemiology Section, Division of Public Health, Alaska Department of Health and Social Services / 15. Violent Crimes Compensation Board, Alaska Department of Public Safety / 16. Alaska Police Standards Council, Alaska Department of Public Safety / 17. Alcoholic Beverage Control Board / 18. Alaska Office of the Ombudsman / 19. State Archives and Records Management Services, Alaska Department of Education / 20. Legislative Research Agency / 21. Legislative Affairs Agency / 22. Alaska State Commission for Human Rights / 23. Parole Board, Alaska Department of Corrections / 24. Alaska Public Offices Commission / 25. Alaska Commission on Judicial Conduct / 26. Alaska Legal Services Corporation / 27. Office of Public Advocacy / 28. Alaska Public Defender Agency / 29. Inde

Statistical Analysis of Composite Spectra

We consider nearest neighbor spacing distributions of composite ensembles of levels. These are obtained by combining independently unfolded sequences of levels containing only few levels each. Two problems arise in the spectral analysis of such data. One problem lies in fitting the nearest neighbor spacing distribution to the histogram of level spacings obtained from the data. We show that the method of Bayesian inference is superior to this procedure. The second problem occurs when one unfolds such short sequences. We show that the unfolding procedure generically leads to an overestimate of the chaoticity parameter. This trend is absent in the presence of long-range level correlations. Thus, composite ensembles of levels from a system with long-range spectral stiffness yield reliable information about the chaotic behavior of the system.Comment: 26 pages, 3 figures; v3: changed conclusions, appendix adde

Statistical Analysis of Precipitation Events

In the present paper we demonstrate the results of a statistical analysis of some characteristics of precipitation events and propose a kind of a theoretical explanation of the proposed models in terms of mixed Poisson and mixed exponential distributions based on the information-theoretical entropy reasoning. The proposed models can be also treated as the result of following the popular Bayesian approach.Comment: 5 pages, 4 figures; ICNAAM 201

Statistical Analysis of Solar Neutrino Data

We calculate with Monte Carlo the goodness of fit and the confidence level of the standard allowed regions for the neutrino oscillation parameters obtained from the fit of the total rates measured in solar neutrino experiments. We show that they are significantly overestimated in the standard method. We also calculate exact allowed regions with correct frequentist coverage. We show that the exact VO, LMA and LOW regions are much larger than the standard ones and merge together giving an allowed band at large mixing angles for all Delta m^2 > 10^{-10} eV^2.Comment: 4 pages. Talk presented by C. Giunti at NOW 2000, Conca Specchiulla (Otranto, Italy), 9-16 Sep. 200

Statistical Shape Analysis using Kernel PCA

©2006 SPIE--The International Society for Optical Engineering. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. The electronic version of this article is the complete one and can be found online at: http://dx.doi.org/10.1117/12.641417DOI:10.1117/12.641417Presented at Image Processing Algorithms and Systems, Neural Networks, and Machine Learning, 16-18 January 2006, San Jose, California, USA.Mercer kernels are used for a wide range of image and signal processing tasks like de-noising, clustering, discriminant analysis etc. These algorithms construct their solutions in terms of the expansions in a high-dimensional feature space F. However, many applications like kernel PCA (principal component analysis) can be used more effectively if a pre-image of the projection in the feature space is available. In this paper, we propose a novel method to reconstruct a unique approximate pre-image of a feature vector and apply it for statistical shape analysis. We provide some experimental results to demonstrate the advantages of kernel PCA over linear PCA for shape learning, which include, but are not limited to, ability to learn and distinguish multiple geometries of shapes and robustness to occlusions

Statistical physics of independent component analysis

Statistical physics is used to investigate independent component analysis with polynomial contrast functions. While the replica method fails, an adapted cavity approach yields valid results. The learning curves, obtained in a suitable thermodynamic limit, display a first order phase transition from poor to perfect generalization.Comment: 7 pages, 1 figure, to appear in Europhys. Lett