Statistical Semantic Classification of Crisis Information

The rise of social media as an information channel during crisis has become key to community response. However, existing crisis awareness applications, often struggle to identify relevant information among the high volume of data that is generated over social platforms. A wide range of statistical features and machine learning methods have been researched in recent years to automatically classify this information. In this paper we aim to complement previous studies by exploring the use of semantics as additional features to identify relevant crisis in- formation. Our assumption is that entities and concepts tend to have a more consistent correlation with relevant and irrelevant information, and therefore can enhance the discrimination power of classifiers. Our results, so far, show that some classification improvements can be obtained when using semantic features, reaching +2.51% when the classifier is applied to a new crisis event (i.e., not in training set)

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 models for market segmentation

It is an essential element of market research that customer preferences are considered and the heterogeneity of these preferences is recognized. By segmenting the market into homogeneous clusters the preferences of customers is addressed. Latent class methodology for conjoint analysis, proposed by Green (2000), is one of the several conjoint segmentation procedures that overcome the limitations of aggregate analysis and priori segmentation. This approach proposes the proportional odds model as a proper statistical model for ordinal categorical data in which the item attributes are included in the linear predictor. The likelihood is maximized through the EM algorithm. This paper considers two extensions of this methodology that incorporate individual characteristics into the models.peer-reviewe

Statistical approach to optimization of the transesterification reaction from sorrel (hibiscus sabdariffa) oil

In an effort to optimize the reaction conditions of biodiesel production from Sorrel seed oil, Response Surface Methodology (RSM) was applied and the effects of reaction temperature, catalyst amount, reaction time and methanol/oil molar ratio, and their reciprocal interactions were ascertained. A total of 30 experimental runs were designed by Central Composite Rotatable Design (CCRD) and carried out. A quadratic polynomial was obtained for predicting the Transesterification process and the ANOVA test showed the model to be significant (p<0.05). The validity of the predicted model was confirmed by carrying out three independent replicates experiments. The actual maximum biodiesel yield obtained was 99.23% (w/w) at methanol/oil molar ratio 6.21, catalyst amount 1.03 (% wt.), reaction temperature 51 oC, and reaction time 63 min. The fuel properties of Hibiscus sabdariffa methylester (HSME) produced were found to be within the ASTM D6751 and DIN EN 14214 biodiesel standards. The fatty acid profile of the HSME revealed that the dominant fatty acids were oleic (58.34%), arachidic (1.55%), palmitic (18.28%) and linoleic (21.19%). Emission assessment revealed 70% reduction of CO at B80, 80% reduction of NO concentration at B40