Databases Useful for Computer Science and Information Science Research: Search.BioPreprint THROUGH SZ




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DATABASE SEARCH RESULTS FOR COMPUTER AND INFORMATION SCIENCE CONTENT :   A THROUGH  B

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DATABASE SEARCH RESULTS FOR COMPUTER AND INFORMATION SCIENCE CONTENT :   C   PART ONE

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DATABASE SEARCH RESULTS FOR COMPUTER AND INFORMATION SCIENCE CONTENT :   C    PART TWO

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DATABASE SEARCH RESULTS FOR COMPUTER AND INFORMATION SCIENCE CONTENT:   D

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DATABASE SEARCH RESULTS FOR COMPUTER AND INFORMATION SCIENCE CONTENT:   E    PART ONE

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DATABASE SEARCH RESULTS FOR COMPUTER AND INFORMATION SCIENCE CONTENT:    E    PART TWO

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DATABASE SEARCH RESULTS FOR COMPUTER AND INFORMATION SCIENCE CONTENT:     F THROUGH G

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DATABASE SEARCH RESULTS FOR COMPUTER AND INFORMATION SCIENCE CONTENT :   O

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DATABASE SEARCH RESULTS FOR COMPUTER AND INFORMATION SCIENCE CONTENT :   P   PART ONE

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DATABASE SEARCH RESULTS FOR COMPUTER AND INFORMATION SCIENCE CONTENT :   P   PART TWO
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DATABASE SEARCH RESULTS FOR COMPUTER AND INFORMATION SCIENCE CONTENT :    PSY THROUGH PZ

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DATABASES USEFUL FOR COMPUTER SCIENCE AND INFORMATION SCIENCE RESEARCH:   R

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DATABASES USEFUL FOR COMPUTER SCIENCE AND INFORMATION SCIENCE RESEARCH:    S THROUGH SCOPUS

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DATABASES USEFUL FOR COMPUTER SCIENCE AND INFORMATION SCIENCE RESEARCH:
SEARCH.BIOPREPRINT THROUGH SZ

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DATABASES USEFUL FOR COMPUTER SCIENCE AND INFORMATION SCIENCE RESEARCH:     T THROUGH Z

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Databases Useful for Computer Science and Information Science Research: 
Search.BioPreprint THROUGH SZ

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"computer science" OR "information science" OR "computer programming" OR informatics OR "data management" OR "information security" OR "network security" OR forensics OR "visual computing" OR "data mining" OR "machine learning" OR "multimedia databases" OR "artificial intelligence"



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42 Results
  1. ... New Results IntelliEppi: Intelligent reaction monitoring and holistic data management system for the molecular biology lab Arthur Neuberger , ... demands for intelligent reaction monitoring, quality control and data management in molecular biology laboratories. To meet such needs, ...
    79K - bioRxiv-collection
  2. In this paper a method for detection of image forgery in lossy compressed digital images known as error level analysis (ELA) is presented and it's noisy components are filtered with automatic wavelet soft-thresholding. With ELA, a lossy compressed image is recompressed...
    PeerJ Preprints
  3. ... annotation with GBOL, an extendable infrastructure for functional data mining View ORCID Profile Jesse C.J. van Dam , ... However, the current format provides limited support for data mining, hampering comparative analyses at large scale. Results: The ...
    87K - bioRxiv-collection
  4. We present a CUDA based implementation of a decision tree construction algorithm within the gradient boosting library XGBoost. The tree construction algorithm is executed entirely on the GPU and shows high performance with a variety of datasets and settings, including...
    PeerJ Preprints
  5. ... pipeline for cancer prediction and biomarker identification using machine learning framework View ORCID Profile Akram Mohammed , Greyson Biegert , ... by the tools available for processing and analysis. Machine learning holds great potential for deciphering these data in ...
    84K - bioRxiv-collection
  6. ... proteins in conjunction with functional annotation allows the exploitation of advanced supervised machine learning techniques for automatic protein function prediction. Methods. In this work, novel shape features ...
    PeerJ Preprints
  7. ... with RNA-Seq data: Can alternative splicing enhance machine learning classifier? Nathan T. Johnson , Andi Dhroso , Katelyn J. ... the RNA-Seq data requires development of new data mining and analytics methods. Supervised machine learning methods are ...
    86K - bioRxiv-collection
  8. ... We describe and experimentally validate a question-asking framework for machine-learned linguistic knowledge about human emotions. Using the Socratic method as a theoretical inspiration, we develop an experimental ...
    PeerJ Preprints
  9. ... for this keyword Advanced Search New Results A machine learning classifier trained on cancer transcriptomes detects NF1 inactivation ... transcriptional landscape of a tumor and allow a machine learning classifier to detect which tumors will benefit from ...
    91K - bioRxiv-collection
  10. ... Feature selection in machine learning is of great interest since it is reckoned as creating more efficient predictive models in several engineering domains. It is even of special importance in the pulp and paper ... //... system; the latter is found to be more precise in predicting the pulp quality. We then combined several data mining algorithms such as genetic algorithm-partial least square regression, along with other statistical methods ...
    PeerJ Preprints
  11. ... Search for this keyword Advanced Search New Results Machine learning analysis identifies Drosophila Grunge/Atrophin as an important ... PILGRM, which analyzes public gene expression compendia using machine learning. We evaluated the top prediction alongside genes involved ...
    83K - bioRxiv-collection
  12. ... specific classifiers on these sets. Then we apply our methodology to a panel of benchmarks of standard machine learning algorithms on typical data sets, demonstrating how it can be used in practice to gain insights into ...
    PeerJ Preprints
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CONTENT SAMPLE
1.
Identifying child abuse through text mining and machine learning
By: Amrit, Chintan; Paauw, Tim; Aly, Robin; et al.
EXPERT SYSTEMS WITH APPLICATIONS   Volume: 88   Pages: 402-418   Published: DEC 1 2017
 
Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
2.
Using Nontraditional Qualitative Data Collection Methods with Vulnerable Forensic Psychiatric Patients: Challenges and Insights
By: Kinney, Penelope
INTERNATIONAL JOURNAL OF QUALITATIVE METHODS   Volume: 16   Issue:   Published: DEC 2017
 
Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
3.
Machine Learning-based system for berth scheduling at bulk terminals
By: Davila de Leon, Alan; Lalla-Ruiz, Eduardo; Melian-Batista, Belen; et al.
EXPERT SYSTEMS WITH APPLICATIONS   Volume: 87   Pages: 170-182   Published: NOV 30 2017
 
Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
4.
Data mining-based variable assessment methodology for evaluating the contribution of knowledge services of a public research institute to business performance of firms
By: Choi, Jeongsub; Kim, Byunghoon; Hahn, Hyuk; et al.
EXPERT SYSTEMS WITH APPLICATIONS   Volume: 84   Pages: 37-48   Published: OCT 30 2017
 Full Text from Publisher
 
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Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
5.
Machine learning models and bankruptcy prediction
By: Barboza, Flavio; Kimura, Herbert; Altman, Edward
EXPERT SYSTEMS WITH APPLICATIONS   Volume: 83   Pages: 405-417   Published: OCT 15 2017
 
 View Abstract
Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
6.
Analyzing undergraduate students' performance using educational data mining
By: Asif, Raheela; Merceron, Agathe; Ali, Syed Abbas; et al.
COMPUTERS & EDUCATION   Volume: 113   Pages: 177-194   Published: OCT 2017

Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
7.
Data mining in educational technology classroom research: Can it make a contribution?
By: Angeli, Charoula; Howard, Sarah K.; Ma, Jun; et al.
COMPUTERS & EDUCATION   Volume: 113   Pages: 226-242   Published: OCT 2017
 
Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
8.
Security and Privacy for Cloud-Based Data Management in the Health Network Service Chain: A Microservice Approach
By: Esposito, Christian; Castiglione, Aniello; Tudorica, Constantin-Alexandru; et al.
IEEE COMMUNICATIONS MAGAZINE   Volume: 55   Issue:   Pages: 102-108   Published: SEP 2017
 
Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
9.
CRIMINAL JUSTICE AND FORENSIC SCIENCE: A MULTIDISCIPLINARY INTRODUCTION
By: Walsh, Dave
BRITISH JOURNAL OF CRIMINOLOGY   Volume: 57   Issue:   Pages: 1270-1272   Published: SEP 2017
 Full Text from Publisher
 
Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
10.
Can Machine Learning Help Fight Fake News?
By: Kompella, Kashyap
ECONTENT   Volume: 40   Issue:   Pages: 40-40   Published: SEP-OCT 2017
 
11.
Machine Learning Approach Using Fractal Electroencephalography Features Predicts Response to Electroconvulsive Therapy
By: Singh, Natashia; Warsi, Mohammed A.
JOURNAL OF ECT   Volume: 33   Issue:   Pages: 216-216   Published: SEP 2017
 
Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
12.
Evaluation of Acute Alcohol Intoxication as the Primary Cause of Death: A Diagnostic Challenge for Forensic Pathologists
By: Li, Rong; Hu, Li; Hu, Lingli; et al.
JOURNAL OF FORENSIC SCIENCES   Volume: 62   Issue:   Pages: 1213-1219   Published: SEP 2017
 Full Text from Publisher
 
 View AbstractView Abstract
Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
13.
A Comparative Taphonomic Analysis of 24 Trophy Skulls from Modern Forensic Cases(,)
By: Yucha, Josephine M.; Pokines, James T.; Bartelink, Eric J.
JOURNAL OF FORENSIC SCIENCES   Volume: 62   Issue:   Pages: 1266-1278   Published: SEP 2017
 Full Text from Publisher
 
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Times Cited: 0
(from Web of Science Core Collection)
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14.
Pragmatic (trial) informatics: a perspective from the NIH Health Care Systems Research Collaboratory
By: Richesson, Rachel L.; Green, Beverly B.; Laws, Reesa; et al.
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION   Volume: 24   Issue:   Pages: 996-1001   Published: SEP 2017
 Full Text from Publisher
 
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Times Cited: 0
(from Web of Science Core Collection)
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15.
Machine Learning, Sentiment Analysis, and Tweets: An Examination of Alzheimer's Disease Stigma on Twitter
By: Oscar, Nels; Fox, Pamela A.; Croucher, Racheal; et al.
JOURNALS OF GERONTOLOGY SERIES B-PSYCHOLOGICAL SCIENCES AND SOCIAL SCIENCES  Volume: 72   Issue:   Pages: 742-751   Published: SEP 2017
 Full Text from Publisher
 
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Times Cited: 1 
(from Web of Science Core Collection)
Usage Count
 
16.
Health informatics: The ownership and use of mobile medical applications among Egyptian patients
By: Mansour, Essam
JOURNAL OF LIBRARIANSHIP AND INFORMATION SCIENCE   Volume: 49   Issue:   Pages: 335-355  Published: SEP 2017
 Full Text from Publisher
 
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Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
17.
machine learning-based method for the large-scale evaluation of the qualities of the urban environment
By: Liu, Lun; Silva, Elisabete A.; Wu, Chunyang; et al.
COMPUTERS ENVIRONMENT AND URBAN SYSTEMS   Volume: 65   Pages: 113-125   Published: SEP 2017
 Full Text from Publisher
 
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Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
18.
Developing news-based Economic Policy Uncertainty index with, unsupervised machine learning
By: Azqueta-Gavaldon, Andres
ECONOMICS LETTERS   Volume: 158   Pages: 47-50   Published: SEP 2017
 Full Text from Publisher
 
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Times Cited: 0
(from Web of Science Core Collection)
Usage Count
 
19.
Evaluating Negative Forensic Evidence: When Do Jurors Treat Absence of Evidence as Evidence of Absence?
By: Thompson, William C.; Scurich, Nicholas; Dioso-Villa, Rachel; et al.
JOURNAL OF EMPIRICAL LEGAL STUDIES   Volume: 14   Issue:   Pages: 569-591   Published: SEP 2017
 Full Text from Publisher
 
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Times Cited: 0
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Usage Count
 
20.
The Adult Male Rape Victim Forensic Description of a Series of 57 Cases
By: Casali, Michelangelo Bruno; Palazzo, Elisa; Blandino, Alberto; et al.
AMERICAN JOURNAL OF FORENSIC MEDICINE AND PATHOLOGY   Volume: 38   Issue:   Pages: 175-179  Published: SEP 2017
 Full Text from Publisher
 
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Social Services Abstracts
411 Results


CONTENT SAMPLE

  • 1

    Artificial Intelligence -- An Aide in Child Protective Service Caseload Control Systems

    Fluke, John D; O'Beirne, Gregory N. Computers in Human Services4.1 -- 2 (1989): 101-109.

    ...for more efficient service delivery through integration with hitartificial

    Cited by (‎4)    




  • 2

    Artificial Intelligence: An Introduction

    Butterfield, William H. Computers in Human Services3.1 -- 2 (1988): 23-35.

    ...hitartificial hitintelligence (AI) for social service administrators & workers.



     

  • 3

    Impacts of Artificial Intelligence

    Boden, Margaret A. Futures16.1 (February 1984): 60-70.

    ...hitartificial hitintelligence is expected over the next decade in areas including
    ...the notion of hitartificial hitintelligence. Modified HA

       


  • 4

    Artificial Intelligence: Implications for Teaching Decision Science

    Santhanam, Radhika; Schniederjans, Marc J. Interfaces21.5 (September 1991): 63-69.

    ...hitartificial hitintelligence (AI), its importance to students of the decision



  • 5

    An Expert System Approach to Rural Development: A Prototype (TIHSO)

    Balachandran, Chandra S; Fisher, Peter F; Stanley, Michael A. Journal of Developing Areas23.2 (January 1989): 259-270.

    ...hitartificial hitintelligence, especially the subbranch of expert systems, for the

    Cited by (‎1)    


  • 6

    Online Buddhist and Christian Responses to Artificial Intelligence

    Tamatea, Laurence. Zygon45.4 (December 2010): 979-1002.

    ...online Christian and Buddhist responses to hitartificial hitintelligence. I review the
    ...Dei informs the online Buddhist response to hitartificial hitintelligence? And to what


  • 7  Michael E. Simulation & Gaming25.1 (March 1994): 88-98.

    Counseling Artificial Intelligence
    hitartificial hitintelligence (AI) & expert systems (ESs) to counseling. Appropriate

    Cited by (‎3)    References (‎38)    




  • 8

    Growth, productivity, and scientific impact of sources* of HIV/AIDS research information, with a focus on eastern and southern Africa

    Onyancha, Omwoyo Bosire. African Journal of AIDS Research7.1 (0, 2008): 55-70.

    Cited by (‎2)    References (‎37)    


  • 9

    USE OF GIS AND DATA MINING TECHNIQUES IN THE DESIGNING OF COMMUNITY-BASED SERVICES FOR THE ELDERLY

    Liu, L; Leu, F. The Gerontologist, suppl. 61st Annual Scientific Meeting "Resilience in an Aging..; Oxford48 (Oct 2008): 24.

    ...hitdata hitmining techniques to explore both social factors and environmental
    ...with hitdata hitmining techniques, to develop a community-based service information
    ...Taichung City, Taiwan, 2. Department of hitComputer hitScience, Tunghai University in

     
  • 10

    Data mining in child welfare

    Schoech, Dick; Quinn, Andrew; Rycraft, Joan R. Child Welfare; Arlington79.5 (Sep/Oct 2000): 633-50.

    ...concepts, processes, techniques, and tools of hitdata hitmining, using statistical and
    ...of training, and high turnover prevail. hitData hitmining, a new field, entails
    ...nearly 80% of companies expected hitdata hitmining to be a critical success factor in


  • 11

    Mining Electronic Health Records Data: Domestic Violence and Adverse Health Effects

    Karakurt, Gunnur; Patel, Vishal; Whiting, Kathleen; Koyutürk, Mehmet. Journal of Family Violence; New York32.1 (Jan 2017): 79-87.

    ...partner violence . Domestic violence . Health consequences . Big hitdata hitmining .
    ...hitData hitmining is made possible by the availability of large collections of
    ...we feel its purpose at this point is to verify that these methods of hitdata hitmining

    References (‎23)    



  • 12

    Psychosocial service needs of pediatric transport accident survivors: Using clinical data-mining to establish demographic and service usage characteristics

    Manguy, Alys-Marie; Joubert, Lynette; Bansemer, Leah. Social Work in Health Care; New York55.8 (Sep 2016): 595-613.

    ...needs of pediatric transport accident survivors: Using clinical hitdata-hitmining to
    ...of demographic and service usage data gained through clinical hitdata hitmining audit
    ...hitdata-hitmining audit of 100 sequentially sampled cases gathering quantitative


  • 13

    Psychosocial service needs of pediatric transport accident survivors: Using clinical data-mining to establish demographic and service usage characteristics

    Manguy, Alys-Marie; Joubert, Lynette; Bansemer, Leah. Social Work in Health Care; New York55.8 (Sep 2016): 595-613.

    ...hitdata hitmining audit and suggesting recommendations for social work service


  • 14

    Clinical data-mining: Learning from practice in international settings

    Lalayants, Marina; Epstein, Irwin; Auslander, Gail K; Chan, Wallace Chi Ho; Fouche, Christa; et al. International Social Work56.6 (November 2013): 775-797.

    ...hitData-hitMining (CDM) -- as a strategy for engaging international practitioners for

    Cited by (‎4)    References (‎76)    


  • 15

    Future Mind: Artificial Intelligence

    Baer, Stephen H. Public Relations Review17.2 (July 1991): 201-202.

  • 16

    A Workshop On Artificial Intelligence // Review

    Canadian Public Policy; Guelph10.4 (Dec 1984): 482.

  • 17

    Using Artificial Intelligence to Model Juvenile Recidivism Patterns

    Brodzinski, James D; Crable, Elaine A; Scherer, Robert F. Computers in Human Services10.4 (0, 1994): 1-18.

    Cited by (‎5)    


  • 18

    Sex-specific patterns and differences in dementia and Alzheimer's disease using informatics approaches

    Ronquillo, Jay Geronimo; Baer, Merritt Rachel; Lester, William T. Journal of Women & Aging; London28.5 (2016): 403-411.

    ...of unprecedented scale and scope by applying hitinformatics approaches to three



  • 19

    Clinical Data-Mining

    Joelson, Richard B. Social Work in Mental Health9.1 (January 2011): 71-72.
    Preview 
  • 20

    Clinical Data-Mining

    Guzzetta, Charles. Journal of Teaching in Social Work30.3 (July 2010): 353-355.

*
Society of Exploration Geophysicists Ebooks
1,800 Results

Content Sample




Combining Machine Learning and Geophysical Inversion for Applied Geophysics
Anya M. ReadingMatthew J. CracknellDaniel J. BombardieriTim Chalke
ASEG Extended Abstracts 2015: 24th International Geophysical Conference and Exhibition: 1-5.



The Rise of the Machines, Analytics, and the Digital Oilfield: ArtificialIntelligence in the Age of Machine Learning and Cognitive Analytics
Kathy BallTristan ArbusUchenna OdiJessamyn Sneed
Unconventional Resources Technology Conference, Austin, Texas, 24-26 July 2017: 410-418.



Machine learning as a tool for geologists
Antoine CatéLorenzo PerozziErwan GloaguenMartin Blouin
The Leading Edge Mar 2017, Vol. 36, No. 3, pp. 215-219
Online Publication Date: March 2017



Application of Artificial Intelligence on Black Shale Lithofacies Prediction in Marcellus Shale, Appalachian Basin
G. Wang*Y. JuC. LiT.R. CarrG. Cheng
Unconventional Resources Technology Conference, Denver, Colorado, 25-27 August 2014: 1970-1980.
Permissions 




Machine learning systems open up access to large volumes of valuable information lying dormant in unstructured documents
Kerry BlinstonHenri Blondelle
The Leading Edge Mar 2017, Vol. 36, No. 3, pp. 257-261
Online Publication Date: March 2017



Machine Learning in Rock Facies Classification: An Application of XGBoost
Licheng ZhangCheng Zhan
International Geophysical Conference, Qingdao, China, 17-20 April 2017: 1371-1374.



Log Analysis Systems Incorporating Artificial Intelligence Techniques - Some Examples
Paul L. Baker
Exploration Geophysics Jun 1989, Vol. 20, No. 1/2, pp. 331-334
Online Publication Date: June 1989



Machine learning assisted velocity autopicking
Kenneth Smith
Permissions 





CannyTEM – a high-resolution transient electromagnetic system based on mobile technology and artificial intelligence
Xing HeRujun Chen*Hongchun YaoHong WuJieting QiuRuijie ShenQiang RenHonghua ShiHai DongShenglong Tan
International Conference on Engineering Geophysics, Al Ain, United Arab Emirates, 15-18 November 2015: 56-59.



Prediction and Analysis of Geomechanical Properties of the Bakken Shale Using Artificial Intelligence and Data Mining
George K. ParapuramMehdi MokhtariJalel Ben Hmida
Unconventional Resources Technology Conference, Austin, Texas, 24-26 July 2017: 2815-2833.



Building a machine learning classifier for iron ore prospectivity in the Yilgarn Craton
Andrew S. MerdithThomas C.W. LandgrebeR. Dietmar Müller
ASEG Extended Abstracts 2015: 24th International Geophysical Conference and Exhibition: 1-4.




Application of artificial intelligence for Euler solutions clustering
Valentine MikhailovArmand GaldeanoMichel DiamentAlexei GvishianiSergei AgayanShamil′ BogoutdinovElena GraevaPascal Sailhac
GEOPHYSICS Jan 2003, Vol. 68, No. 1, pp. 168-180
Online Publication Date: January-February 2003



Workshop 4 — Artificial intelligence
SEG Technical Program Expanded Abstracts 1988: 1341-1342.

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Total Organic Carbon Prediction in Shale Gas Reservoirs using the Artificial intelligence with a comparative study between Fuzzy Logic and Neural Network
Sid-Ali Ouadfeul*Leila Aliouane
14th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 3-6 August 2015: 1390-1393.



Time-lapse reservoir property change estimation from seismic using machine learning
Jun CaoBaishali Roy
The Leading Edge Mar 2017, Vol. 36, No. 3, pp. 234-238
Online Publication Date: March 2017



machine learning approach to facies classification using well logs
Paolo BestaginiVincenzo LipariStefano Tubaro
SEG Technical Program Expanded Abstracts 2017: 2137-2142.
Abstract | References | PDF (1216 KB) | PDF w/Links (1225 KB) | Permissions 

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Show Abstract



Image analysis of rock thin section based on machine learning
Zheng MaShichen Gao
International Geophysical Conference, Qingdao, China, 17-20 April 2017: 844-847.



Distributed collaborative prediction: Results of the machine learningcontest
Matt HallBrendon Hall
The Leading Edge Mar 2017, Vol. 36, No. 3, pp. 267-269
Online Publication Date: March 2017



What can machine learning do for seismic data processing? An interpolation application
Yongna JiaJianwei Ma
GEOPHYSICS May 2017, Vol. 82, No. 3, pp. V163-V177
Online Publication Date: May-June 2017






Sociological Abstracts 
2,826 Results

CONTENT SAMPLE


  • Building Machine Learning models for a law enforcement triage tool to detect illicit images

    McCooey, Kristen L. ProQuest, Ann Arbor MI, 0, 2013. AAI1516558.

    ...Vision and hitMachine hitLearning techniques for detecting skin tone pixels in

    References (‎33)    



  • 2

    Reducing Incongruity of Perceptions Related to Information Risk: Dialogical Action Research in Organizations

    Sedlack, Derek J. ProQuest, Ann Arbor MI, 0, 2013. AAI3524253.

    ...hitinformation hitsecurity has recently shifted toward more robust, organizationally
    ...hitinformation hitsecurity gaps. This dissertation applies dialogical action research



  • 3

    Detecting financial statement fraud: Three essays on fraud predictors, multi-classifier combination and fraud detection using data mining

    Perols, Johan L. ProQuest, Ann Arbor MI, 0, 2009. AAI3347362.


  • 4

    Timing, Sequencing, and Quantum of Life Course Events: A Machine Learning Approach

    Billari, Francesco C; Furnkranz, Johannes; Prskawetz, Alexia. European Journal of Population/Revue europeenne de demographie22.1 (0, 2006): 37-65.

    ...hitmachine hitlearning techniques, using ideas from a core research area in the
    ...to adulthood. We briefly introduce hitmachine hitlearning algorithms to build decision



  • 5

    Understanding Information Security Culture in an Organization: An Interpretive Case Study

    Bess, Donald Arlo. ProQuest, Ann Arbor MI, 0, 2013. AAI3526079.

    ...hitinformation hitsecurity program in place protecting those information systems. It

    References (‎67)    



  • 6

    The Role of Trait Affect in the Information Security Behavior of Home Users.

    Dupuis, Marc J. ProQuest, Ann Arbor MI, 0, 2015. AAI3631744.

    ...generally stable type of affect, has on the hitinformation hitsecurity behavior of
    ...data and files. In this study, the role of trait affect in the hitinformation
    ...trait negative affect have on the hitinformation hitsecurity behavior of home users is



  • 7

    Blaming the User in Medical Informatics: The Cultural Nature of Scientific Practice

    Forsythe, Diana E. Knowledge and Society: The Anthropology of Science and Technology9 (0, 1992): 95-111.

    ...hitartificial hitintelligence (AI) labs & field studies in the scientific community

    Cited by (‎4)    


  • 8

    Learning cyber trust using a triadic functioning analysis: a qualitative approach

    Tsai, Yuan Hui; Lin, Chieh-peng; Chiu, Chou-kang; Joe, Sheng-wuu. Quality and Quantity; Dordrecht44.6 (Oct 2010): 1165-1174.

    ...hitcomputer hitscience, hitinformation hitscience and some social sciences (Kling 1999).
    ...elds, including hitcomputer hitscience, hitinformation hitscience and some social sciences.

    Cited by (‎1)    References (‎45)    



  • 9

    Timing, Sequencing, and Quantum of Life Course Events: A Machine Learning Approach

    Billari, Francesco C; Johannes Fürnkranz; Prskawetz, Alexia. European Journal of Population; Dordrecht22.1 (2006): 37-65.

    ...basic notions of the hitmachine hitlearning and hitdata hitmining approach, which are
    .... hitMachine hitlearning and hitdata hitmining systems are used for analysing
    ...in hitmachine hitlearning and hitdata hitmining can be found in Michalski et al

    Cited by (‎7)    



  • 10

    Detecting tension in online communities with computational Twitter analysis

    Burnap, Pete; Rana, Omer F; Avis, Nick; Williams, Matthew; Housley, William; et al. Technological Forecasting and Social Change; New York95 (Jun 2015): 96.

    ...rules; sentiment analysis; and hitmachine hitlearning methods was tested as a possible
    ...hitmachine hitlearning approaches and a sentiment analysis tool at classifying tension


  • 11

    Universal informatics: Building cyberinfrastructure, interoperating the geosciences

    Ribes, David. ProQuest Information and Learning, Ann Arbor MI, April 2007.

    ...of multidisciplinary collaborations of domain and hitcomputer hitscience. At the

    • Abstract/Details
    Preview 
  • 12

    Distributed Artificial Intelligence Meets Machine Learning: Learning in Multi-Agent Environments

    Scott, Paul D. Journal of Artificial Societies and Social Simulation3.3 (0, 2000).

  • 13

    Themes of Human Sciences and Artificial Intelligence

    Alternate title: Donnees de sciences humaines et intelligence artificielle
    Selz-Lauriere, Marion. L'Homme30 (October 1990): 143-150.

    ...argued that while hitcomputer hitscience has penetrated most areas of modern life, &
    ...for this incompetence are outlined: hitcomputer hitscience cannot be applied perfectly
    ...work before utilizing hitcomputer hitscience, choosing between simplifying the system,



  • 14

    All the world's a stage: A playable model of social interaction inspired by dramaturgical analysis

    McCoy, Joshua Allen. ProQuest, Ann Arbor MI, 0, 2013. AAI3522515.

    ...arise when using social hitartificial hitintelligence systems in real-time

    Cited by (‎1)    References (‎171)    



     
  • 15

    Science, Gender, and a Feminist Sociology of Science: The Case of Artificial Intelligence

    Jansen, Sue Curry. American Sociological Association, (0, 1987).

    ...gendering of hitartificial hitintelligence: (1) The salient traits of the cognitive
    ...selected texts on hitartificial hitintelligence is undertaken with special attention


  • 16

    From Expert Systems to Knowledge-Based Companies: How the AI Industry Negotiated a Market for Knowledge

    Vaux, Janet. Social Epistemology15.3 (July 2001): 231-245.

    ...hitartificial hitintelligence industry on the commodification of knowledge in
    ...hitintelligence & the market's construction of the usefulness of hitartificial



  • 17

    Unraveling Iconicity: Data-Driven Modeling of Iconic Gestures in Humans and Virtual Humans

    Tepper, Paul A. ProQuest, Ann Arbor MI, 0, 2015. AAI3627217.

    ...a novel application of techniques from hitmachine hitlearning and hitdata hitmining, I found



  • 18

    Computable Models of the Law (Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence)

    Giardini, Francesca. Journal of Artificial Societies and Social Simulation12.2 (March 2009).
     



  • 19

    Institutionalization of information security: Case of the Indonesian banking sector

    Nasution, Muhamad Faisal Fariduddin Attar.. ProQuest, Ann Arbor MI, 0, 2013. AAI3523906.

    ...hitinformation hitsecurity in the banking sector. This study is important to pursue
    ...breach. The study argues that hitinformation hitsecurity governance and practices

    References (‎148)    

       

    • 20

      Multi-Agent-Based Simulation IX (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence)

      Neumann, Martin. Journal of Artificial Societies and Social Simulation12.4 (October 2009).


    • 21

      Expert Systems and IDSS: Advantages and Consequences for Organizations

      Alternate title: Systemes experts et SIAD: enjeux et consequences pour les organisations
      Pomerol, Jean-Charles. Technologies de l' Information et Societe3.1 (0, 1990): 37-64.

      ...hitartificial hitintelligence were coupled during the 1980s with numerous changes in



    • 22

      Why AI Is Not a Science

      Matteuzzi, Maurizio. Stanford Humanities Review4.2 (0, 1995): 207-218.

      ...hitArtificial hitintelligence (AI) has often escaped definition. Its issues intersect


    • 23

      Investigating the Impact of Self-Control and Deterrents on Noncompliant Information Security Behavior

      Chuma, Ramadhan J. ProQuest, Ann Arbor MI, 0, 2013. AAI3539757.

      ...hitinformation hitsecurity policy and rules is a serious impediment to the

      References (‎159)    


    • 24

      Building Better Models: Prediction, Replication, and Machine Learning in the Social Sciences

      Hindman, Matthew. Annals of the American Academy of Political and Social Science; Thousand Oaks659 (May 2015): 48.

      ...datasets. This article offers an overview of hitmachine hitlearning methods
      ...addition to novel algorithms, hitmachine hitlearning places great emphasis on model

      Cited by (‎3)    References (‎22)    


    • 25

      Evaluating the use of assurance cases for digital forensics.

      Jones, Connie. ProQuest, Ann Arbor MI, 0, 2014. AAI1554661.

      ...field of computer security, digital hitforensics is playing an increasingly
      ...hitforensics investigator, to high-level claims of criminal behavior. There exists
      ...arguments for the conclusion of an investigation based on digital hitforensics

      References (‎23)    



    *
    SpringerLink 
    1,508,023 Results


    CONTENT SAMPLE

    Content Type

    1. Chapter 928,791
    2. Conference Paper 562,332
    3. Article 470,430
    4. Reference Work Entry 71,983
    5. Book 32,815
    6. Conference Proceedings 13,685
    7. Protocol 3,723
    8. Journal 225
    9. Book Series 56
    10. Reference Work 56

    Discipline


    1. Computer Science 769,077
    2. Engineering 175,733
    3. Medicine & Public Health 94,831
    4. Mathematics 94,006
    5. Biomedicine 47,721

    Subdiscipline


    1. Artificial Intelligence (incl. Robotics) 372,579
    2. Computer Communication Networks 216,010
    3. Information Systems Applications (incl. Internet) 198,857
    4. Information Storage and Retrieval 137,547
    5. Algorithm Analysis and Problem Complexity 137,280

    Language


    1. English 1,424,041
    2. German 81,458
    3. French 1,631
    4. Italian 468
    5. Dutch 311

    1. Accounting for Social, Spatial, and Textual Interconnections

      This is a chapter about what link analysis and data mining can do for criminal investigation. It is ... turning to case studies of link analysis and data mining, we take a broad view of digital ... resources and ...

      Dr. Ephraim Nissan in Computer Applications for Handling Legal E… (2012)

    2. Book and Reference Work

      Encyclopedia of Machine Learning and Data Mining

      Encyclopedia of Machine Learning and Data Mining

      Claude Sammut, Geoffrey I. Webb (2017)

    3. Book and Conference Proceedings

      Machine Learning and Data Mining in Pattern Recognition

      Machine Learning and Data Mining in Pattern Recognition

      First International Workshop, MLDM’99 Leipzig, Germany, September 16–18, 1999 Proceedings

      Petra Perner, Maria Petrou in Lecture Notes in Computer Science (1999)

    4. Book and Conference Proceedings

      Machine Learning and Data Mining in Pattern Recognition

      5th International Conference, MLDM 2007, Leipzig, Germany, July 18-20, 2007. Proceedings

      Petra Perner in Lecture Notes in Computer Science (2007)

    5. Book and Conference Proceedings

      Machine Learning and Data Mining in Pattern Recognition

      Second International Workshop, MLDM 2001 Leipzig, Germany, July 25–27, 2001 Proceedings

      Petra Perner in Lecture Notes in Computer Science (2001)

    6. Book and Conference Proceedings

      Machine Learning and Data Mining in Pattern Recognition

      Machine Learning and Data Mining in Pattern Recognition

      11th International Conference, MLDM 2015, Hamburg, Germany, July 20-21, 2015, Proceedings

      Petra Perner in Lecture Notes in Computer Science (2015)

    7. Book and Conference Proceedings

      Machine Learning and Data Mining in Pattern Recognition

      Third International Conference, MLDM 2003 Leipzig, Germany, July 5–7, 2003 Proceedings

      Petra Perner, Azriel Rosenfeld in Lecture Notes in Computer Science (2003)

    8. Book and Conference Proceedings

      Machine Learning and Data Mining Approaches to Climate Science

      Proceedings of the 4th International Workshop on Climate Informatics

      Valliappa Lakshmanan, Eric Gilleland (2015)

    9. Book and Conference Proceedings

      Visual Computing

      Integrating Computer Graphics with Computer Vision

      Professor Tosiyasu L. Kunii in CG International Series (1992)

    10. Book

      Machine Learning and Data Mining for Computer Security

      Methods and Applications

      Marcus A. Maloof BS, MS, PhD in Advanced Information and Knowledge Processing (2006)

    11. Book and Conference Proceedings

      Machine Learning and Data Mining in Pattern Recognition

      Machine Learning and Data Mining in Pattern Recognition

      13th International Conference, MLDM 2017, New York, NY, USA, July 15-20, 2017, Proceedings

      Petra Perner in Lecture Notes in Computer Science (2017)

    12. Book and Conference Proceedings

      Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

      Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

      6th European Conference, EvoBIO 2008, Naples, Italy, March 26-28, 2008. Proceedings

      Elena Marchiori, Jason H. Moore in Lecture Notes in Computer Science (2008)

    13. Book and Conference Proceedings

      Evolutionary Computation,Machine Learning and Data Mining in Bioinformatics

      5th European Conference, EvoBIO 2007, Valencia, Spain, April 11-13, 2007. Proceedings

      Elena Marchiori, Jason H. Moore in Lecture Notes in Computer Science (2007)

    14. Book and Conference Proceedings

      Machine Learning and Data Mining in Pattern Recognition

      12th International Conference, MLDM 2016, New York, NY, USA, July 16-21, 2016, Proceedings

      Petra Perner in Lecture Notes in Computer Science (2016)

    15. Book

      Principles and Theory for Data Mining and Machine Learning

      Principles and Theory for Data Mining and Machine Learning

      Bertrand Clarke, Ernest Fokoue in Springer Series in Statistics (2009)

    16. Book and Conference Proceedings

      Machine Learning and Data Mining in Pattern Recognition

      Machine Learning and Data Mining in Pattern Recognition

      7th International Conference, MLDM 2011, New York, NY, USA, August 30 – September 3, 2011. Proceedings

      Petra Perner in Lecture Notes in Computer Science (2011)

    17. Book and Conference Proceedings

      Machine Learning and Data Mining in Pattern Recognition

      Machine Learning and Data Mining in Pattern Recognition

      4th International Conference, MLDM 2005, Leipzig, Germany, July 9-11, 2005. Proceedings

      Petra Perner, Atsushi Imiya in Lecture Notes in Computer Science (2005)

    18. Book and Conference Proceedings

      Machine Learning and Data Mining in Pattern Recognition

      Machine Learning and Data Mining in Pattern Recognition

      9th International Conference, MLDM 2013, New York, NY, USA, July 19-25, 2013. Proceedings

      Petra Perner in Lecture Notes in Computer Science (2013)

    19. Book and Conference Proceedings

      Machine Learning and Data Mining in Pattern Recognition

      10th International Conference, MLDM 2014, St. Petersburg, Russia, July 21-24, 2014. Proceedings

      Petra Perner in Lecture Notes in Computer Science (2014)

    20. Book and Conference Proceedings

      Machine Learning and Data Mining in Pattern Recognition

      Machine Learning and Data Mining in Pattern Recognition

      8th International Conference, MLDM 2012, Berlin, Germany, July 13-20, 2012. Proceedings

      Petra Perner in Lecture Notes in Computer Science (2012)

    previous Page of 75,402

  •                  Book and Conference Proceedings

    Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

    Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

    10th European Conference, EvoBIO 2012, Málaga, Spain, April 11-13, 2012. Proceedings

    Mario Giacobini, Leonardo Vanneschi in Lecture Notes in Computer Science (2012)

  • Book and Conference Proceedings

    Machine Learning and Data Mining in Pattern Recognition

    Machine Learning and Data Mining in Pattern Recognition

    6th International Conference, MLDM 2009, Leipzig, Germany, July 23-25, 2009. Proceedings

    Petra Perner in Lecture Notes in Computer Science (2009)

  • Book and Conference Proceedings

    Privacy and Security Issues in Data Mining and Machine Learning

    Privacy and Security Issues in Data Mining and Machine Learning

    International ECML/PKDD Workshop, PSDML 2010, Barcelona, Spain, September 24, 2010. Revised Selected Papers

    Christos Dimitrakakis in Lecture Notes in Computer Science (2011)

  • Chapter

    Knowledge Management, Data Mining, and Text Mining in Medical Informatics

    In this chapter we provide a broad overview of selected knowledge management, data mining, and text mining techniques and their use ... . We first introduce five major paradigms for machine learning and data anal...

    Hsinchun Chen, Sherrilynne S. Fuller, Carol Friedman, William Hersh in Medical Informatics (2005)

    Download PDF (1794 KB)
  • Book and Conference Proceedings

    Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

    11th European Conference, EvoBIO 2013, Vienna, Austria, April 3-5, 2013. Proceedings

    Leonardo Vanneschi, William S. Bush in Lecture Notes in Computer Science (2013)

  • Book and Conference Proceedings

    Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

    Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

    9th European Conference, EvoBIO 2011, Torino, Italy, April 27-29, 2011. Proceedings

    Clara Pizzuti, Marylyn D. Ritchie in Lecture Notes in Computer Science (2011)

  • Book and Conference Proceedings

    Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

    Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

    7th European Conference, EvoBIO 2009 Tübingen, Germany, April 15-17, 2009 Proceedings

    Clara Pizzuti, Marylyn D. Ritchie in Lecture Notes in Computer Science (2009)

  • Book and Conference Proceedings

    Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

    Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

    8th European Conference, EvoBIO 2010, Istanbul, Turkey, April 7-9, 2010. Proceedings

    Clara Pizzuti, Marylyn D. Ritchie in Lecture Notes in Computer Science (2010)

  • Book and Conference Proceedings

    Advances in Visual Computing

    Advances in Visual Computing

    Third International Symposium, ISVC 2007, Lake Tahoe, NV, USA, November 26-28, 2007, Proceedings, Part II

    George Bebis, Richard Boyle, Bahram Parvin in Lecture Notes in Computer Science (2007)

  • Book and Conference Proceedings

    Advances in Visual Computing

    Advances in Visual Computing

    Third International Symposium, ISVC 2007, Lake Tahoe, NV, USA, November 26-28, 2007, Proceedings, Part I

    George Bebis, Richard Boyle, Bahram Parvin in Lecture Notes in Computer Science (2007)

  • Book and Conference Proceedings

    Advances in Visual Computing

    Advances in Visual Computing

    4th International Symposium, ISVC 2008, Las Vegas, NV, USA, December 1-3, 2008. Proceedings, Part I

    George Bebis, Richard Boyle, Bahram Parvin in Lecture Notes in Computer Science (2008)

  • Book and Conference Proceedings

    Advances in Visual Computing

    Advances in Visual Computing

    4th International Symposium, ISVC 2008, Las Vegas, NV, USA, December 1-3, 2008. Proceedings, Part II

    George Bebis, Richard Boyle, Bahram Parvin in Lecture Notes in Computer Science (2008)

  • Book

    Automatic Quantum Computer Programming

    Automatic Quantum Computer Programming

    A Genetic Programming Approach

    Lee Spector in Genetic Programming (2004)

  • Book

    Automatic Quantum Computer Programming

    Automatic Quantum Computer Programming

    A Genetic Programming Approach

    Lee Spector in Genetic Programming (2007)

  • No Access

    Book

    Mastering Computer Programming

    Mastering Computer Programming

    P. E. Gosling in Macmillan Master Series (1990)

  • Book and Conference Proceedings

    Advances in Visual Computing

    Advances in Visual Computing

    12th International Symposium, ISVC 2016, Las Vegas, NV, USA, December 12-14, 2016, Proceedings, Part II

    George Bebis, Richard Boyle, Bahram Parvin in Lecture Notes in Computer Science (2016)

  • Book and Conference Proceedings

    Advances in Visual Computing

    Advances in Visual Computing

    12th International Symposium, ISVC 2016, Las Vegas, NV, USA, December 12-14, 2016, Proceedings, Part I

    George Bebis, Richard Boyle, Bahram Parvin in Lecture Notes in Computer Science (2016)

  • Chapter

    Knowledge Discovery and Data Mining in Biomedical Informatics: The Future Is in Integrative, Interactive Machine Learning Solutions

    Biomedical research is drowning in data, yet starving for knowledge. Current challenges in biomedical research and clinical practice include information overload – the need to combine vast amounts of structured, ...

    Andreas Holzinger, Igor Jurisica in Interactive Knowledge Discovery and Data M… (2014)


  • Book

    Visual Computing

    Visual Computing

    The Integration of Computer Graphics, Visual Perception and Imaging

    Markus Groß in Computer Graphics: Systems and Applications (1994)

  • Book

    Axiomatising the Logic of Computer Programming

    Axiomatising the Logic of Computer Programming

    Robert Goldblatt in Lecture Notes in Computer Science (1982)


  • *

    STAT!Ref 
     "computer science" OR "information science" OR "computer programming" OR informatics OR "data management" OR "information security" OR "network security" OR forensics OR "visual computing" OR "data mining" OR "machine learning" OR "multimedia databases"
    1271 Results

    CONTENT SAMPLE

    1.
    Stage-based interventions for smoking cessation
    In: ESSENTIAL EVIDENCE PLUS™ & AHFS DI® ESSENTIALS™ » Cochrane Database of Systematic Reviews » 2010 Cochranes » October... in their non-stage-based versions. The evidence was unclear for telephone counselling, interactive computer programmes or training of doctors or lay supporters. This uncertainty may be due in part to smaller numbers ...

    2.


    At least 1/3 of adults illiterate or marginally literate
    In: ESSENTIAL EVIDENCE PLUS™ & AHFS DI® ESSENTIALS™ » POEMs (Patient-Oriented Evidence That Matters) » 1999 POEMs » May
    ... health literacy. Reading ability declined dramatically with age. ¶ David Slawson, MD ¶ Director of Information Sciences ¶ University of Virginia Health System ¶ Charlottesville, VA ¶

    3.

    April
    In: ESSENTIAL EVIDENCE PLUS™ & AHFS DI® ESSENTIALS™ » POEMs (Patient-Oriented Evidence That Matters) » 1998 POEMs
    ... tolerated and no change in cognition or functional status occurred. ¶ David Slawson, MD ¶ Director of Information Sciences ¶ University of Virginia Health System ¶ Charlottesville, VA ¶

     

    *
    Statistical Insight 
    Results 10,351


    CONTENT SAMPLE

    • Library and Information Science Education Statistical Report, 2009
      (350 p.) Published: 2010, Source: Association for Library and Information Science Education, Record Number: 2010 SRI A3235-1
      Data Summary: Library/info science school enrollment, staff and student characteristics, finances, and curricula, by school and degree program, 2009 annual rpt

    • 2

      Regional Computer Forensics Laboratory: Annual Report for FY2012
      (64 p.) Published: 2013, Source: Federal Bureau of Investigation, SuDoc: J1.14/31:2012, Record Number: 2013 ASI 6224-17
      Data Summary: Computer forensics labs, digital forensics services, training, and funding allocations, FY2012, annual rpt

    • 3

      Regional Computer Forensics Laboratory: Annual Report for FY2011
      (60 p.) Published: 2012, Source: Federal Bureau of Investigation, SuDoc: J1.14/31:2011, Record Number: 2012 ASI 6224-17
      Data Summary: Computer forensics labs, digital forensics services, training, and funding allocations, FY2011, annual rpt

    • 4

      Regional Computer Forensics Laboratory: Annual Report for FY2007
      (68 p.) Published: 2008, Source: Federal Bureau of Investigation, Record Number: 2008 ASI 6224-17
      Data Summary: Computer forensics laboratories, and media items examined and other activities, training, and allocations, by region, FY2004-07, annual rpt

    • 5


      Regional Computer Forensics Laboratory: Annual Report for FY2006
      (68 p.) Published: 2007, Source: Federal Bureau of Investigation, Record Number: 2007 ASI 6224-17
      Data Summary: Computer forensics laboratories, and media items examined and other activities, training, and allocations, by region, FY2003-06, annual rpt

    • 6

      Regional Computer Forensics Laboratory: Annual Report for FY2008
      (54 p.) Published: 2009, Source: Federal Bureau of Investigation, Record Number: 2009 ASI 6224-17
      Data Summary: Computer forensics laboratories, and media items examined and other activities, training, and allocations, FY2008, annual rpt

    • 7

      Regional Computer Forensics Laboratory: Annual Report for FY2010
      (56 p.) Published: 2011, Source: Federal Bureau of Investigation, SuDoc: J1.14/31:2010, Record Number: 2011 ASI 6224-17
      Data Summary: Computer forensics labs, and media items examined and other activities, training, and allocations, FY2010, annual rpt

    • 8

      National Forensic DNA Study Report: Final Report
      (472 p.) Published: 2005, Source: Department of Justice, Record Number: 2005 ASI 6008-57
      Data Summary: Forensic crime labs DNA testing capabilities and potential for use in resolving unsolved cases 2003 survey rpt

    • 9

      Regional Computer Forensics Laboratory: Annual Report for FY2009
      (72 p.) Published: 2010, Source: Federal Bureau of Investigation, Record Number: 2010 ASI 6224-17
      Data Summary: Computer forensics labs, and media items examined and other activities, training, and allocations, FY2009, annual rpt

    • 10

      Sexual Assault: Information on Training, Funding, and the Availability of Forensic Examiners
      (44 p.) Published: 2017, Source: Government Accountability Office, SuDoc: GA1.13:GAO-16-334, Record Number: 2017 ASI 26108-3251
      Data Summary: Justice Dept grants for training sexual assault forensic examiners, by grant program and State, various periods 2013-16, GAO rpt

    • 11

    • Data Mining: Federal Efforts Cover a Wide Range of Uses
      (71 p.) Published: 2004, Source: General Accounting Office, SuDoc: GA1.13:GAO-04-548, Record Number: 2004 ASI 26108-416
      Data Summary: Computer data gathering and analysis efforts of Fed Govt, and system purpose and status, by agency, as of Apr 2004, GAO rpt

    • 12

      Publicly Funded Forensic Crime Laboratories: Resources and Services, 2014 : Bureau of Justice Statistics Bulletin
      (12 p.) Published: 2016, Source: Office of Justice Programs (Department of Justice), SuDoc: J29.11:250151, Record Number: 2016 ASI 6066-25.266
      Data Summary: Forensic crime lab services and resources, by jurisdiction type, selected years 2002-14

    • 13

      FY2003 Report to Congress on Federal Government Information Security Management
      (78 p.) Published: 2004, Source: Office of Management and Budget, Record Number: 2004 ASI 104-44
      Data Summary: Info technology security requirements of Federal Information Security Management Act, compliance by agencies, FY2003, annual rpt

    • 14

      Census of Publicly Funded Forensic Crime Laboratories, 2009 : Bureau of Justice Statistics Bulletin
      (14 p.) Published: 2012, Source: Office of Justice Programs (Department of Justice), Record Number: 2012 ASI 6066-25.226
      Data Summary: Forensic crime lab funding, employment, and requests for services, by jurisdiction type, selected years 2002-09


    • 15

      Peru Statistical Compendium, 2014 [Compendio Estadistico del Peru, 2014]
      Published: 2015, Source: Peru National Institute of Statistics and Informatics (Peru), Record Number: 2015 IIS 7260-S1
      Data Summary: Peru socioecon detailed indicators, 2014 Peru Natl Inst of Statistics and Informatics annual rpt

    • 16

      Library and Information Science Education Statistical Report, 2005
      (367 p.) Published: 2008, Source: Association for Library and Information Science Education, Record Number: 2008 SRI A3235-1
      Data Summary: Library/info science school enrollment, staff and student characteristics, finances, and curricula, by school and degree program, 2005 annual rpt

    • 17

      Peru Statistical Compendium, 2012
      Published: 2013, Source: Peru National Institute of Statistics and Informatics (Peru), Record Number: 2013 IIS 7260-S1
      Data Summary: Peru socioecon detailed indicators, 2012 Peru National Inst of Statistics and Informatics annual rpt

    • 18

      Follow-Up Audit of the Bureau of Alcohol, Tobacco, Firearms and Explosives Forensic Science Laboratories Workload Management : U.S. Department of Justice, Office of the Inspector General, Audit Division: Audit Reports
      (89 p.) Published: 2006, Source: Department of Justice, Record Number: 2006 ASI 6006-7.4
      Data Summary: Forensic crime labs workload of Bureau of Alcohol, Tobacco, Firearms, and Explosives, by lab, case type, processing time, and other characteristics, various periods FY98-2005

    • 19

      Publicly Funded Forensic Crime Laboratories: Quality Assurance Practices, 2014 : Bureau of Justice Statistics Bulletin
      (11 p.) Published: 2016, Source: Office of Justice Programs (Department of Justice), SuDoc: J29.11:250152, Record Number: 2016 ASI 6066-25.265
      Data Summary: Forensic crime lab quality assurance practices, by jurisdiction type, accreditation status, and other characteristics, selected years 2002-14

    • 20

      Research Data Management Services : SPEC Kits
      (220 p.) Published: 2014, Source: Association of Research Libraries, Record Number: 2014 SRI A3365-14.61
      Data Summary: Research data mgmt services of research libraries, incl mgmt plan consultation and training for researchers, archiving practices, staff and roles, and funding, May 2013 survey



      *
      Synthesis Digital Library of Engineering and Computer Science
       
       
      Search Results: 583 matches found 
      Search Query: [All: "computer science"] OR [All: "information science"] OR [All: "computer programming"] OR [All: informatics]OR [All: "data management"] OR [All: "information security"] OR [All: "network security"] OR [All: forensics] OR [All: "visual computing"] OR [All: "data mining"] OR [All: "machine learning"] OR [All: "multimedia databases"] OR [All: "artificial intelligence"] 



      CONTENT SAMPLE

      Results page 1 of 30 
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      1.
      Quantum Computer Science
      Marco LanzagortaJeffreyUhlmann
      Synthesis Lectures on Quantum Computing Jan 2008, Vol. 1, No. 1, Pages 1-124

      2.
      Ensemble Methods in Data Mining: Improving Accuracy Through Combining Predictions
      Giovanni SeniJohn F. Elder
      Synthesis Lectures on Data Mining and Knowledge Discovery Jan 2010, Vol. 2, No. 1, Pages 1-126

      3.
      Lifelong Machine Learning
      Zhiyuan ChenBing Liu


      4.
      Analysis Techniques for Information Security
      Anupam DattaSomesh JhaNinghui LiDavid MelskiThomas Reps
      Synthesis Lectures on Information Security, Privacy, and Trust Apr 2010, Vol. 2, No. 1, Pages 1-164
       


      5.
      Spatial Data Management
      Nikos Mamoulis
      Synthesis Lectures on Data Management Nov 2011, Vol. 3, No. 6, Pages 1-149


      6.
      User-Centered Data Management
      Tiziana CatarciAlan DixStephen KimaniGiuseppe Santucci
      Synthesis Lectures on Data Management Jan 2010, Vol. 2, No. 1, Pages 1-106


      7.
      Peer-to-Peer Data Management
      Karl Aberer
      Synthesis Lectures on Data Management May 2011, Vol. 3, No. 2, Pages 1-150


      8.
      Markov Logic: An Interface Layer for Artificial Intelligence
      Pedro DomingosDaniel Lowd
      Synthesis Lectures on Artificial Intelligence and Machine Learning Jan 2009, Vol. 3, No. 1, Pages 1-155


      9.
      A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence
      Nikos Vlassis
      Synthesis Lectures on Artificial Intelligence and Machine Learning Jan 2007, Vol. 1, No. 1, Pages 1-71


      10.
      Social Informatics Evolving
      Pnina FichmanMadelyn R. SanfilippoHoward Rosenbaum
      Synthesis Lectures on Information Concepts, Retrieval, and Services Sep 2015, Vol. 7, No. 5, Pages 1-108


      11.
      Statistical Relational Artificial Intelligence: Logic, Probability, and Computation
      Luc De RaedtKristian KerstingSriraam NatarajanDavid Poole
      Synthesis Lectures on Artificial Intelligence and Machine Learning Mar 2016, Vol. 10, No. 2, Pages 1-189


      12.
      Tensor Voting: A Perceptual Organization Approach to Computer Vision and Machine Learning
      Philippos MordohaiGérard Medioni
      Synthesis Lectures on Image, Video, and Multimedia Processing Jan 2006, Vol. 2, No. 1, Pages 1-136

      13.
      Dictionary Learning in Visual Computing
      Qiang Zhang Baoxin Li
      Synthesis Lectures on Image, Video, and Multimedia Processing May 2015, Vol. 8, No. 2, Pages 1-151


      14.
      From Tool to Partner: The Evolution of Human-Computer Interaction
      Jonathan Grudin
      Synthesis Lectures on Human-Centered Informatics Jan 2017, Vol. 10, No. 1, Pages i-183

      15.
      Representation Discovery using Harmonic Analysis
      Sridhar Mahadevan
      Synthesis Lectures on Artificial Intelligence and Machine Learning Jan 2008, Vol. 2, No. 1, Pages 1-147


      16.
      A Short Introduction to Preferences: Between ArtificialIntelligence and Social Choice
      Francesca RossiKristen Brent VenableToby Walsh
      Synthesis Lectures on Artificial Intelligence and Machine Learning Jul 2011, Vol. 5, No. 4, Pages 1-102

      17.
      Modeling and Data Mining in Blogosphere
      Nitin Agarwal Huan Liu
      Synthesis Lectures on Data Mining and Knowledge Discovery Jan 2009, Vol. 1, No. 1, Pages 1-109

      18.
      Access Control in Data Management Systems
      Elena Ferrari
      Synthesis Lectures on Data Management Jan 2010, Vol. 2, No. 1, Pages 1-117

      19.
      Replicated Data Management for Mobile Computing
      Douglas B. Terry
      Synthesis Lectures on Mobile and Pervasive Computing Jan 2008, Vol. 3, No. 1, Pages 1-94


      20.
      Geographical Design: Spatial Cognition and Geographical Information Science
      Stephen C. Hirtle
      Synthesis Lectures on Human-Centered Informatics Mar 2011, Vol. 4, No. 1, Pages 1-67



























































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