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@article{Kaluza2010,
abstract = {Transportation networks play a crucial role in human mobility, the exchange of goods and the spread of invasive species. With 90 per cent of world trade carried by sea, the global network of merchant ships provides one of the most important modes of transportation. Here, we use information about the itineraries of 16 363 cargo ships during the year 2007 to construct a network of links between ports. We show that the network has several features that set it apart from other transportation networks. In particular, most ships can be classified into three categories: bulk dry carriers, container ships and oil tankers. These three categories do not only differ in the ships' physical characteristics, but also in their mobility patterns and networks. Container ships follow regularly repeating paths whereas bulk dry carriers and oil tankers move less predictably between ports. The network of all ship movements possesses a heavy-tailed distribution for the connectivity of ports and for the loads transported on the links with systematic differences between ship types. The data analysed in this paper improve current assumptions based on gravity models of ship movements, an important step towards understanding patterns of global trade and bioinvasion.},
archivePrefix = {arXiv},
arxivId = {1001.2172},
author = {Kaluza, Pablo and K{\"{o}}lzsch, Andrea and Gastner, Michael T. and Blasius, Bernd},
doi = {10.1098/rsif.2009.0495},
eprint = {1001.2172},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Kaluza et al.{\_}2010{\_}The complex network of global cargo ship movements(2).pdf:pdf;:E$\backslash$:/bjoer/Documents/Mendeley/Kaluza et al.{\_}2010{\_}The complex network of global cargo ship movements.pdf:pdf},
isbn = {1742-5662 (Electronic)$\backslash$r1742-5662 (Linking)},
issn = {1742-5689},
journal = {Journal of the Royal Society, Interface / the Royal Society},
keywords = {bioinvasion,cargo ships,complex network,transportation},
number = {48},
pages = {1093--1103},
pmid = {20086053},
title = {{The complex network of global cargo ship movements.}},
url = {http://arxiv.org/abs/1001.2172},
volume = {7},
year = {2010}
}
@misc{Granovetter1973,
abstract = {Analysis of social networks is suggested as a tool for linking micro and macro levels of sociological theory. The procedure is illustrated by elaboration of the macro implications of one aspect of small-scale interaction: the strength of dyadic ties. It is argued that the degree of overlap of two individuals' friendship networks varies directly with the strength of their tie to one another. The impact of this principle on diffusion of influence and information, mobility opportunity, and community organization is explored. Stress is laid on the cohesive power of weak ties. Most network models deal, implicitly, with strong ties, thus confining their applicability to small, well-defined groups. Emphasis on weak ties lends itself to discussion of relations between groups and to analysis of segments of social structure not easily defined in terms of primary groups.},
author = {Granovetter, Mark S.},
booktitle = {American Journal of Sociology},
number = {6},
pages = {1360},
title = {{The Strength of Weak Ties}},
volume = {78},
year = {1973}
}
@article{Beckman2002a,
abstract = {According to the Annual Reports of the International Maritime Bureau on Piracy and Armed Robbery Against Ships for calendar years 1998, 1999, and 2000, there has been a dramatic increase in the number of reported incidents of piracy and armed robbery against ships in waters in Southeast Asia, especially in the Malacca Strait and in Indonesian waters. Very few of the incidents in Southeast Asia are “piracy” as defined in international law because they took place in waters under the sovereignty of a coastal state. Nevertheless, many of the incidents posed serious threats to the safety of international maritime navigation. Some were offences under the 1988 Convention for the Suppression of Acts Against the Safety of International Maritime Navigation. Some were also major criminal hijacks involving international organized crime. There has been considerable action at both the global and re- gional levels to attempt to deal with this threat to the safety of international naviga- tion. This article analyzes the reported incidents and the attempts by the interna- tional community to deal with the problem. The article concludes with various rec- ommendations on steps that should be taken by the international community and States in Southeast Asia to combat piracy and armed robbery against ships.},
annote = {Beckman's recommendations entered into creating{\&}nbsp;the variables{\&}nbsp;in the IMB and NGIA database. He{\&}nbsp;categorizes attacks Equipment etc.{\&}nbsp;},
author = {Beckman, Robert C},
doi = {10.1080/0090832029005480},
isbn = {9781849804844},
issn = {0090-8320},
journal = {Ocean Development {\&} International Law},
number = {3},
pages = {317--341},
title = {{Combatting Piracy and Armed Robbery Against Ships in Southeast Asia : The Way Forward}},
volume = {33},
year = {2002}
}
@article{Marchione2013,
author = {Marchione, E. and Johnson, S. D.},
doi = {10.1177/0022427812469113},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Marchione, Johnson{\_}2013{\_}Spatial, Temporal and Spatio-Temporal Patterns of Maritime Piracy.pdf:pdf},
issn = {0022-4278},
journal = {Journal of Research in Crime and Delinquency},
keywords = {crime,prevention,quantitative research,research methods,victimization},
number = {4},
pages = {504--524},
title = {{Spatial, Temporal and Spatio-Temporal Patterns of Maritime Piracy}},
url = {http://jrc.sagepub.com/cgi/doi/10.1177/0022427812469113},
volume = {50},
year = {2013}
}
@article{Mejia.2009,
author = {Mejia, Maximo Q and Cariou, Pierre and Wolff, Francois-Charles},
doi = {10.1080/13504850701222186},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Mejia, Cariou, Wolff{\_}2009{\_}Is maritime piracy random.pdf:pdf},
issn = {1350-4851},
journal = {Applied Economics Letters},
number = {9},
pages = {891--895},
title = {{Is maritime piracy random?}},
volume = {16},
year = {2009}
}
@article{Daxecker2015,
author = {Daxecker, Ursula E. and Prins, Brandon C.},
doi = {10.1111/fpa.12014},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Daxecker, Prins{\_}2015{\_}The New Barbary Wars Forecasting Maritime Piracy.pdf:pdf},
isbn = {0001414100},
issn = {17438586},
journal = {Foreign Policy Analysis},
number = {1},
pages = {23--44},
title = {{The New Barbary Wars: Forecasting Maritime Piracy}},
url = {http://doi.wiley.com/10.1111/fpa.12014},
volume = {11},
year = {2015}
}
@article{ElioMarchione2014,
author = {{Elio Marchione}, Shane D Johnson and Alan Wilson},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Elio Marchione{\_}2014{\_}Modelling Maritime Piracy A Spatial Approach.pdf:pdf},
journal = {Journal of Artificial Societies and Social Simulation},
title = {{Modelling Maritime Piracy : A Spatial Approach}},
volume = {17},
year = {2014}
}
@article{Mastrobuoni2014,
author = {Mastrobuoni, Giovanni},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Mastrobuoni{\_}2014{\_}Crime is Terribly Revealing Information Technology and Police Productivity ∗.pdf:pdf},
keywords = {as mario venturi and,as well,crime,for providing the data,h1,h41,his sta ff for,i would,i would like to,jel classification codes,k42,l23,me,o33,of milan,police,predictive policing,quasi-experiment,questore di milano,robberies and policing with,sharing their knowledge on,thank the police chief},
title = {{Crime is Terribly Revealing : Information Technology and Police Productivity ∗}},
year = {2014}
}
@article{Short.2008,
abstract = {Motivated by empirical observations of spatio-temporal clusters of crime across a wide variety of urban settings, we present a model to study the emergence, dynamics, and steady-state properties of crime hotspots. We focus on a two-dimensional lattice model for residential burglary, where each site is characterized by a dynamic attractiveness variable, and where each criminal is represented as a random walker. The dynamics of criminals and of the attractiveness field are coupled to each other via specific biasing and feedback mechanisms. Depending on parameter choices, we observe and describe several regimes of aggregation, including hotspots of high criminal activity. On the basis of the discrete system, we also derive a continuum model; the two are in good quantitative agreement for large system sizes. By means of a linear stability analysis we are able to determine the parameter values that will lead to the creation of stable hotspots. We discuss our model and results in the context of established criminological and sociological findings of criminal behavior.},
author = {Short, Martin B and D'Orsogna, M B and Pasqour, V B and Tita, George B and Brantingham, Paul J and Bertozzi, Andrea L and Chayes, Lincoln B},
doi = {10.1142/S0218202508003029},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Short et al.{\_}2008{\_}A statistical model of criminal behavior.pdf:pdf},
isbn = {0218-2025},
issn = {0218-2025},
journal = {Mathematical Models and Methods in Applied Sciences},
pages = {1249--1267},
title = {{A Statistical Model of Criminal Behavior}},
url = {http://www.worldscientific.com/doi/abs/10.1142/S0218202508003029},
volume = {18, Suppl.},
year = {2008}
}
@article{Twyman-Ghoshal2014,
annote = {Describtion of how data was merged.},
author = {Twyman-Ghoshal, Anamika a. and Pierce, Glenn},
doi = {10.1093/bjc/azu019},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Twyman-Ghoshal, Pierce{\_}2014{\_}The Changing Nature of Contemporary Maritime Piracy.pdf:pdf},
issn = {0007-0955},
journal = {British Journal of Criminology},
keywords = {contemporary maritime piracy database,maritime piracy,somalia},
number = {4},
pages = {652--672},
title = {{The Changing Nature of Contemporary Maritime Piracy}},
url = {http://bjc.oxfordjournals.org/lookup/doi/10.1093/bjc/azu019},
volume = {54},
year = {2014}
}
@article{Byreddy2015,
author = {Byreddy, Raghavender Reddy and Life, Globe and Company, Accident Insurance and Minukuri, Anvesh Reddy},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Byreddy et al.{\_}2015{\_}Analyzing Marine Piracy from Structured {\&} Unstructured data using SAS ® Text Miner PART I-INSIGHTS FROM UNSTRUCTURED.pdf:pdf},
number = {2014},
pages = {1--12},
title = {{Analyzing Marine Piracy from Structured {\&} Unstructured data using SAS ® Text Miner PART I-INSIGHTS FROM UNSTRUCTURED DATA}},
year = {2015}
}
@article{Greengard.2012,
author = {Greengard, Samuel},
doi = {10.1145/2093548.2093555},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Greengard{\_}2012{\_}Policing the future.pdf:pdf},
issn = {00010782},
journal = {Communications of the ACM},
keywords = {Introduction,LAPD,predictive policing},
mendeley-tags = {Introduction,LAPD,predictive policing},
number = {3},
pages = {19},
title = {{Policing the future}},
volume = {55},
year = {2012}
}
@article{Wang2013,
abstract = {Our goal is to automatically detect patterns of crime. Among a large set of crimes that happen every year in a major city, it is challeng- ing, time-consuming, and labor-intensive for crime analysts to determine which ones may have been committed by the same individual(s). If auto- mated, data-driven tools for crime pattern detection are made available to assist analysts, these tools could help police to better understand pat- terns of crime, leading to more precise attribution of past crimes, and the apprehension of suspects. To do this, we propose a pattern detection algorithm called Series Finder, that grows a pattern of discovered crimes from within a database, starting from a “seed” of a few crimes. Series Finder incorporates both the common characteristics of all patterns and the unique aspects of each specific pattern, and has had promising re- sults on a decade’s worth of crime pattern data collected by the Crime Analysis Unit of the Cambridge Police Department.},
author = {Wang, Tong and Rudin, Cynthia and Wagner, Daniel and Sevieri, Rich},
doi = {10.1007/978-3-642-40994-3{\_}33},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Wang et al.{\_}2013{\_}Learning to detect patterns of crime.pdf:pdf},
isbn = {9783642409936},
issn = {03029743},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
keywords = {Pattern detection,crime data mining,predictive policing},
number = {PART 3},
pages = {515--530},
title = {{Learning to detect patterns of crime}},
volume = {8190 LNAI},
year = {2013}
}
@article{Stomakhin.2011,
author = {Stomakhin, Alexey and Short, Martin B and Bertozzi, Andrea L},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Stomakhin, Short, Bertozzi{\_}2011{\_}Reconstruction of missing data in social networks based on temporal patterns of interactions.pdf:pdf},
journal = {Inverse Problems},
number = {11},
pages = {115013},
title = {{Reconstruction of missing data in social networks based on temporal patterns of interactions}},
url = {http://stacks.iop.org/0266-5611/27/i=11/a=115013},
volume = {27},
year = {2011}
}
@book{Casella2006,
abstract = {Review From the reviews: .,."There are interesting and non-standard topics that are not usually included in a first course in measture-theoretic probability including Markov Chains and MCMC, the bootstrap, limit theorems for martingales and mixing sequences, Brownian motion and Markov processes. The material is well-suported with many end-of-chapter problems." D.L. McLeish for Short Book Reviews of the ISI, December 2006 "The reader sees not only how measure theory is used to develop probability theory, but also how probability theory is used in applications. a The discourse is delivered in a theorem proof format and thus is better suited for classroom a . The authors prose is generally well thought out a . will make an attractive choice for a two-semester course on measure and probability, or as a second course for students with a semester of measure or probability theory under their belt." (Peter C. Kiessler, Journal of the American Statistical Association, Vol. 102 (479), 2007) "The book is a well written self-contained textbook on measure and probability theory. It consists of 18 chapters. Every chapter contains many well chosen examples and ends with several problems related to the earlier developed theory (some with hints). a At the very end of the book there is an appendix collecting necessary facts from set theory, calculus and metric spaces. The authors suggest a few possibilities on how to use their book." (Kazimierz Musial, Zentralblatt MATH, Vol. 1125 (2), 2008) "The title of the book consists of the names of its two basic parts. The booka (TM)s third part is comprised of some special topics from probability theory. a The authors suggest using the book intwo-semester graduate programs in statistics or a one-semester seminar on special topics. The material of the book is standard a is clear, comprehensive and a {\~{}}without being intimidatinga (TM)." (Rimas NorvaiAa, Mathematical Reviews, Issue 2007 f) Product Description This is a graduate level textbook on measure theory and probability theory. The book can be used as a text for a two semester sequence of courses in measure theory and probability theory, with an option to include supplemental material on stochastic processes and special topics. It is intended primarily for first year Ph.D. students in mathematics and statistics although mathematically advanced students from engineering and economics would also find the book useful. Prerequisites are kept to the minimal level of an understanding of basic real analysis concepts such as limits, continuity, differentiability, Riemann integration, and convergence of sequences and series. A review of this material is included in the appendix. The book starts with an informal introduction that provides some heuristics into the abstract concepts of measure and integration theory, which are then rigorously developed. The first part of the book can be used for a standard real analysis course for both mathematics and statistics Ph.D. students as it provides full coverage of topics such as the construction of Lebesgue-Stieltjes measures on real line and Euclidean spaces, the basic convergence theorems, L p spaces, signed measures, Radon-Nikodym theorem, Lebesgue's decomposition theorem and the fundamental theorem of Lebesgue integration on R, product spaces and product measures, and Fubini-Tonelli theorems. It also provides an elementary introduction to Banach and Hilbert spaces, convolutions, Fourier series and Fourier and Plancherel transforms. Thus part I would be particularly useful for students in a typical Statistics Ph.D. program if a separate course on real analysis is not a standard requirement. Part II (chapters 6-13) provides full coverage of standard graduate level probability theory. It starts with Kolmogorov's probability model and Kolmogorov's existence theorem. It then treats thoroughly the laws of large numbers including renewal theory and ergodic theorems with applications and then weak convergence of probability distributions, characteristic functions, the Levy-Cramer continuity theorem and the central limit theorem as well as stable laws. It ends with conditional expectations and conditional probability, and an introduction to the theory of discrete time martingales. Part III (chapters 14-18) provides a modest coverage of discrete time Markov chains with countable and general state spaces, MCMC, continuous time discrete space jump Markov processes, Brownian motion, mixing sequences, bootstrap methods, and branching processes. It could be used for a topics/seminar course or as an introduction to stochastic processes. From the reviews: "...There are interesting and non-standard topics that are not usually included in a first course in measture-theoretic probability including Markov Chains and MCMC, the bootstrap, limit theorems for martingales and mixing sequences, Brownian motion and Markov processes. The material is well-suported with many end-of-chapter problems." D.L. McLeish for Short Book Reviews of the ISI, December 2006},
author = {Casella, George and Fienberg, Stephen and Olkin, Ingram},
booktitle = {Design},
doi = {10.1016/j.peva.2007.06.006},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Casella, Fienberg, Olkin{\_}2006{\_}An Introduction to Statistical Learning.pdf:pdf},
isbn = {9780387781884},
issn = {01621459},
pages = {618},
pmid = {10911016},
title = {{An Introduction to Statistical Learning}},
url = {http://books.google.com/books?id=9tv0taI8l6YC},
volume = {102},
year = {2006}
}
@article{Grover2007,
abstract = {Police analysts are required to unravel the complexities in data to assist operational personnel in arresting offenders and directing crime prevention strategies. However, the volume of crime that is being committed and the awareness of modern criminals make this a daunting task. The ability to analyse this amount of data with its inherent complexities without using computational support puts a strain on human resources. This paper examines the current techniques that are used to predict crime and criminality. Over time, these techniques have been refined and have achieved limited success. They are concentrated into three categories: statistical methods, these mainly relate to the journey to crime, age of offending and offending behaviour; techniques using geographical information systems that identify crime hot spots, repeat victimisation, crime attractors and crime generators; a miscellaneous group which includes machine learning techniques to identify patterns in criminal behaviour and studies involving re- offending. The majority of current techniques involve the prediction of either a single offender's criminality or a single crime type's next offence. These results are of only limited use in practical policing. It is our contention that Knowledge Discovery in Databases should be used on all crime types together with offender data, as a whole, to predict crime and criminality within a small geographical area of a police force.},
author = {Grover, Vikas and Adderley, Richard and Bramer, Max},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Grover, Adderley, Bramer{\_}2007{\_}Review of current crime prediction techniques.pdf:pdf},
isbn = {1-84628-665-4},
journal = {Applications and innovations in intelligent systems XIV},
pages = {233--237},
title = {{Review of current crime prediction techniques}},
volume = {c},
year = {2007}
}
@article{Kiourktsoglou2012,
author = {Kiourktsoglou, George and Coutroubis, Alec D.},
doi = {10.1007/s13437-012-0023-4},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Kiourktsoglou, Coutroubis{\_}2012{\_}Is Somali piracy a random phenomenon.pdf:pdf},
issn = {1651-436X},
journal = {WMU Journal of Maritime Affairs},
number = {1},
pages = {51--70},
title = {{Is Somali piracy a random phenomenon?}},
url = {http://link.springer.com/10.1007/s13437-012-0023-4},
volume = {11},
year = {2012}
}
@article{Mcclendon2015,
author = {Mcclendon, Lawrence and Meghanathan, Natarajan},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Mcclendon, Meghanathan{\_}2015{\_}U SING M ACHINE L EARNING A LGORITHMS TO A NALYZE C RIME D ATA.pdf:pdf},
number = {1},
pages = {1--12},
title = {{Using Machine Learning Algorithms to Analyze Crime Data}},
volume = {2},
year = {2015}
}
@article{Hanson2010,
abstract = {Allozyme variation of aspartate-aminotransferase locus Aat 1 is analysed in the land snail Cochlicopa lubrica (O. F. Muller, 1774). Two alleles, denoted '20' and '80', have been found in 29 Central European populations investigated. This species reproduces under a high rate of self-fertilization. Only three out of 787 individuals were heterozygous (enzyme pattern Aat 1 '20'/'80'). The homozygous individuals with Aat 1 '80' were frequent in moist and shady habitats. In exposed and open habitats, however, the homozygous individuals with Aat 1 '20' occurred frequently. These results give strong evidence for habitat-specific selection inferred from allozyme variation. Moreover, a tight interlocus correlation of isocitrate-dehydrogenase patterns (Idh 1) and Aat 1 patterns has been observed. Two groups of homozygous genotypes are commonly found: (1) the group Idh 1 '145'/Aat 1 '80', and (2) the group Idh 1 '155'/Aat 1 '20'. The Aat data for Cochlicopa lubrica are complemented by morphometric measurements of the shells. The homozygous types of Aat 1 '20' (common in exposed/open habitats) possessed, on average, slightly smaller shells than the homozygous types with Aat 1 '80' (common in moist/shady habitats). This slight mean difference in shell size might be due to the living conditions in the habitats. In the last part of the study, the allozyme variation of snails was assessed for spatial selection processes, and a compilation of the available papers is shown.},
author = {Hanson, Stephanie},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Hanson{\_}2010{\_}Combating Maritime Piracy.pdf:pdf},
issn = {00222933},
journal = {Council on Foreign Relations Backgrounder},
number = {2},
pages = {185--199},
title = {{Combating Maritime Piracy}},
url = {http://www.cfr.org/publication/18376/},
volume = {35},
year = {2010}
}
@inproceedings{Wang2013a,
abstract = {Many crimes can happen every day in a major city, and fig-uring out which ones are committed by the same individualor group is an important and dicult data mining challenge.To do this, we propose a pattern detection algorithm calledSeries Finder, that grows a pattern of discovered crimes fromwithin a database, starting from a “seed” of a few crimes. Se-ries Finder incorporates both the common characteristics ofall patterns and the unique aspects of each specific pattern.We compared Series Finder with classic clustering and clas-sification models applied to crime analysis. It has promisingresults on a decade’s worth of crime pattern data from theCambridge Police Department.},
author = {Wang, Tong and Rudin, Cynthia and Wagner, Daniel and Sevieri, Rich},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Wang et al.{\_}2013{\_}Detecting Patterns of Crime with Series Finder.pdf:pdf},
isbn = {9781577356288},
keywords = {AAAI Technical Report WS-13-17},
pages = {140--142},
title = {{Detecting Patterns of Crime with Series Finder.}},
url = {http://web.mit.edu/rudin/www/WangRuWaSeAAAI13.pdf},
year = {2013}
}
@article{Wang2013,
abstract = {Our goal is to automatically detect patterns of crime. Among a large set of crimes that happen every year in a major city, it is challeng- ing, time-consuming, and labor-intensive for crime analysts to determine which ones may have been committed by the same individual(s). If auto- mated, data-driven tools for crime pattern detection are made available to assist analysts, these tools could help police to better understand pat- terns of crime, leading to more precise attribution of past crimes, and the apprehension of suspects. To do this, we propose a pattern detection algorithm called Series Finder, that grows a pattern of discovered crimes from within a database, starting from a “seed” of a few crimes. Series Finder incorporates both the common characteristics of all patterns and the unique aspects of each specific pattern, and has had promising re- sults on a decade’s worth of crime pattern data collected by the Crime Analysis Unit of the Cambridge Police Department.},
author = {Wang, Tong and Rudin, Cynthia and Wagner, Daniel and Sevieri, Rich},
doi = {10.1007/978-3-642-40994-3{\_}33},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Wang et al.{\_}2013{\_}Learning to detect patterns of crime.pdf:pdf},
isbn = {9783642409936},
issn = {03029743},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
keywords = {Pattern detection,crime data mining,predictive policing},
number = {PART 3},
pages = {515--530},
title = {{Learning to detect patterns of crime}},
volume = {8190 LNAI},
year = {2013}
}
@article{Hanson2010,
abstract = {Allozyme variation of aspartate-aminotransferase locus Aat 1 is analysed in the land snail Cochlicopa lubrica (O. F. Muller, 1774). Two alleles, denoted '20' and '80', have been found in 29 Central European populations investigated. This species reproduces under a high rate of self-fertilization. Only three out of 787 individuals were heterozygous (enzyme pattern Aat 1 '20'/'80'). The homozygous individuals with Aat 1 '80' were frequent in moist and shady habitats. In exposed and open habitats, however, the homozygous individuals with Aat 1 '20' occurred frequently. These results give strong evidence for habitat-specific selection inferred from allozyme variation. Moreover, a tight interlocus correlation of isocitrate-dehydrogenase patterns (Idh 1) and Aat 1 patterns has been observed. Two groups of homozygous genotypes are commonly found: (1) the group Idh 1 '145'/Aat 1 '80', and (2) the group Idh 1 '155'/Aat 1 '20'. The Aat data for Cochlicopa lubrica are complemented by morphometric measurements of the shells. The homozygous types of Aat 1 '20' (common in exposed/open habitats) possessed, on average, slightly smaller shells than the homozygous types with Aat 1 '80' (common in moist/shady habitats). This slight mean difference in shell size might be due to the living conditions in the habitats. In the last part of the study, the allozyme variation of snails was assessed for spatial selection processes, and a compilation of the available papers is shown.},
author = {Hanson, Stephanie},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Hanson{\_}2010{\_}Combating Maritime Piracy.pdf:pdf},
issn = {00222933},
journal = {Council on Foreign Relations Backgrounder},
number = {2},
pages = {185--199},
title = {{Combating Maritime Piracy}},
url = {http://www.cfr.org/publication/18376/},
volume = {35},
year = {2010}
}
@book{Casella2006,
abstract = {Review From the reviews: .,."There are interesting and non-standard topics that are not usually included in a first course in measture-theoretic probability including Markov Chains and MCMC, the bootstrap, limit theorems for martingales and mixing sequences, Brownian motion and Markov processes. The material is well-suported with many end-of-chapter problems." D.L. McLeish for Short Book Reviews of the ISI, December 2006 "The reader sees not only how measure theory is used to develop probability theory, but also how probability theory is used in applications. a The discourse is delivered in a theorem proof format and thus is better suited for classroom a . The authors prose is generally well thought out a . will make an attractive choice for a two-semester course on measure and probability, or as a second course for students with a semester of measure or probability theory under their belt." (Peter C. Kiessler, Journal of the American Statistical Association, Vol. 102 (479), 2007) "The book is a well written self-contained textbook on measure and probability theory. It consists of 18 chapters. Every chapter contains many well chosen examples and ends with several problems related to the earlier developed theory (some with hints). a At the very end of the book there is an appendix collecting necessary facts from set theory, calculus and metric spaces. The authors suggest a few possibilities on how to use their book." (Kazimierz Musial, Zentralblatt MATH, Vol. 1125 (2), 2008) "The title of the book consists of the names of its two basic parts. The booka (TM)s third part is comprised of some special topics from probability theory. a The authors suggest using the book intwo-semester graduate programs in statistics or a one-semester seminar on special topics. The material of the book is standard a is clear, comprehensive and a {\~{}}without being intimidatinga (TM)." (Rimas NorvaiAa, Mathematical Reviews, Issue 2007 f) Product Description This is a graduate level textbook on measure theory and probability theory. The book can be used as a text for a two semester sequence of courses in measure theory and probability theory, with an option to include supplemental material on stochastic processes and special topics. It is intended primarily for first year Ph.D. students in mathematics and statistics although mathematically advanced students from engineering and economics would also find the book useful. Prerequisites are kept to the minimal level of an understanding of basic real analysis concepts such as limits, continuity, differentiability, Riemann integration, and convergence of sequences and series. A review of this material is included in the appendix. The book starts with an informal introduction that provides some heuristics into the abstract concepts of measure and integration theory, which are then rigorously developed. The first part of the book can be used for a standard real analysis course for both mathematics and statistics Ph.D. students as it provides full coverage of topics such as the construction of Lebesgue-Stieltjes measures on real line and Euclidean spaces, the basic convergence theorems, L p spaces, signed measures, Radon-Nikodym theorem, Lebesgue's decomposition theorem and the fundamental theorem of Lebesgue integration on R, product spaces and product measures, and Fubini-Tonelli theorems. It also provides an elementary introduction to Banach and Hilbert spaces, convolutions, Fourier series and Fourier and Plancherel transforms. Thus part I would be particularly useful for students in a typical Statistics Ph.D. program if a separate course on real analysis is not a standard requirement. Part II (chapters 6-13) provides full coverage of standard graduate level probability theory. It starts with Kolmogorov's probability model and Kolmogorov's existence theorem. It then treats thoroughly the laws of large numbers including renewal theory and ergodic theorems with applications and then weak convergence of probability distributions, characteristic functions, the Levy-Cramer continuity theorem and the central limit theorem as well as stable laws. It ends with conditional expectations and conditional probability, and an introduction to the theory of discrete time martingales. Part III (chapters 14-18) provides a modest coverage of discrete time Markov chains with countable and general state spaces, MCMC, continuous time discrete space jump Markov processes, Brownian motion, mixing sequences, bootstrap methods, and branching processes. It could be used for a topics/seminar course or as an introduction to stochastic processes. From the reviews: "...There are interesting and non-standard topics that are not usually included in a first course in measture-theoretic probability including Markov Chains and MCMC, the bootstrap, limit theorems for martingales and mixing sequences, Brownian motion and Markov processes. The material is well-suported with many end-of-chapter problems." D.L. McLeish for Short Book Reviews of the ISI, December 2006},
author = {Casella, George and Fienberg, Stephen and Olkin, Ingram},
booktitle = {Design},
doi = {10.1016/j.peva.2007.06.006},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Casella, Fienberg, Olkin{\_}2006{\_}An Introduction to Statistical Learning.pdf:pdf},
isbn = {9780387781884},
issn = {01621459},
pages = {618},
pmid = {10911016},
title = {{An Introduction to Statistical Learning}},
url = {http://books.google.com/books?id=9tv0taI8l6YC},
volume = {102},
year = {2006}
}
@article{Kiourktsoglou2012,
author = {Kiourktsoglou, George and Coutroubis, Alec D.},
doi = {10.1007/s13437-012-0023-4},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Kiourktsoglou, Coutroubis{\_}2012{\_}Is Somali piracy a random phenomenon.pdf:pdf},
issn = {1651-436X},
journal = {WMU Journal of Maritime Affairs},
number = {1},
pages = {51--70},
title = {{Is Somali piracy a random phenomenon?}},
url = {http://link.springer.com/10.1007/s13437-012-0023-4},
volume = {11},
year = {2012}
}
@article{Short.2008,
author = {Short, Martin B and D'ORSOGNA, Maria R and Pasour, Virginia B and Tita, George E and Brantingham, Paul J and Bertozzi, Andrea L and Chayes, Lincoln B},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Short et al.{\_}2008{\_}A statistical model of criminal behavior.pdf:pdf},
journal = {Mathematical Models and Methods in Applied Sciences},
number = {supp01},
pages = {1249--1267},
title = {{A statistical model of criminal behavior}},
volume = {18},
year = {2008}
}
@article{Daxecker2015,
author = {Daxecker, Ursula E. and Prins, Brandon C.},
doi = {10.1111/fpa.12014},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Daxecker, Prins{\_}2015{\_}The New Barbary Wars Forecasting Maritime Piracy.pdf:pdf},
isbn = {0001414100},
issn = {17438586},
journal = {Foreign Policy Analysis},
number = {1},
pages = {23--44},
title = {{The New Barbary Wars: Forecasting Maritime Piracy}},
url = {http://doi.wiley.com/10.1111/fpa.12014},
volume = {11},
year = {2015}
}
@article{ElioMarchione2014,
author = {{Elio Marchione}, Shane D Johnson and Alan Wilson},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Elio Marchione{\_}2014{\_}Modelling Maritime Piracy A Spatial Approach.pdf:pdf},
journal = {Journal of Artificial Societies and Social Simulation},
title = {{Modelling Maritime Piracy : A Spatial Approach}},
volume = {17},
year = {2014}
}
@article{Stomakhin.2011,
author = {Stomakhin, Alexey and Short, Martin B and Bertozzi, Andrea L},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Stomakhin, Short, Bertozzi{\_}2011{\_}Reconstruction of missing data in social networks based on temporal patterns of interactions.pdf:pdf},
journal = {Inverse Problems},
number = {11},
pages = {115013},
title = {{Reconstruction of missing data in social networks based on temporal patterns of interactions}},
url = {http://stacks.iop.org/0266-5611/27/i=11/a=115013},
volume = {27},
year = {2011}
}
@article{Greengard.2012,
author = {Greengard, Samuel},
doi = {10.1145/2093548.2093555},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Greengard{\_}2012{\_}Policing the future.pdf:pdf},
issn = {00010782},
journal = {Communications of the ACM},
keywords = {Introduction,LAPD,predictive policing},
mendeley-tags = {Introduction,LAPD,predictive policing},
number = {3},
pages = {19},
title = {{Policing the future}},
volume = {55},
year = {2012}
}
@article{Mastrobuoni2014,
author = {Mastrobuoni, Giovanni},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Mastrobuoni{\_}2014{\_}Crime is Terribly Revealing Information Technology and Police Productivity ∗.pdf:pdf},
keywords = {as mario venturi and,as well,crime,for providing the data,h1,h41,his sta ff for,i would,i would like to,jel classification codes,k42,l23,me,o33,of milan,police,predictive policing,quasi-experiment,questore di milano,robberies and policing with,sharing their knowledge on,thank the police chief},
number = {December},
title = {{Crime is Terribly Revealing : Information Technology and Police Productivity ∗}},
year = {2014}
}
@article{Kaluza2010a,
abstract = {Transportation networks play a crucial role in human mobility, the exchange of goods and the spread of invasive species. With 90 per cent of world trade carried by sea, the global network of merchant ships provides one of the most important modes of transportation. Here, we use information about the itineraries of 16 363 cargo ships during the year 2007 to construct a network of links between ports. We show that the network has several features that set it apart from other transportation networks. In particular, most ships can be classified into three categories: bulk dry carriers, container ships and oil tankers. These three categories do not only differ in the ships' physical characteristics, but also in their mobility patterns and networks. Container ships follow regularly repeating paths whereas bulk dry carriers and oil tankers move less predictably between ports. The network of all ship movements possesses a heavy-tailed distribution for the connectivity of ports and for the loads transported on the links with systematic differences between ship types. The data analysed in this paper improve current assumptions based on gravity models of ship movements, an important step towards understanding patterns of global trade and bioinvasion.},
archivePrefix = {arXiv},
arxivId = {1001.2172},
author = {Kaluza, Pablo and K{\"{o}}lzsch, Andrea and Gastner, Michael T and Blasius, Bernd},
doi = {10.1098/rsif.2009.0495},
eprint = {1001.2172},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Kaluza et al.{\_}2010{\_}The complex network of global cargo ship movements.pdf:pdf},
isbn = {1742-5662 (Electronic)$\backslash$r1742-5662 (Linking)},
issn = {1742-5689},
journal = {Journal of the Royal Society, Interface / the Royal Society},
keywords = {bioinvasion,cargo ships,complex network,transportation},
number = {48},
pages = {1093--1103},
pmid = {20086053},
title = {{The complex network of global cargo ship movements.}},
volume = {7},
year = {2010}
}
@article{Mejia.2009,
author = {Mejia, Maximo Q and Cariou, Pierre and Wolff, Francois-Charles},
doi = {10.1080/13504850701222186},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Mejia, Cariou, Wolff{\_}2009{\_}Is maritime piracy random.pdf:pdf},
issn = {1350-4851},
journal = {Applied Economics Letters},
number = {9},
pages = {891--895},
title = {{Is maritime piracy random?}},
volume = {16},
year = {2009}
}
@article{Marchione2013,
author = {Marchione, E. and Johnson, S. D.},
doi = {10.1177/0022427812469113},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Marchione, Johnson{\_}2013{\_}Spatial, Temporal and Spatio-Temporal Patterns of Maritime Piracy.pdf:pdf},
issn = {0022-4278},
journal = {Journal of Research in Crime and Delinquency},
keywords = {crime,prevention,quantitative research,research methods,victimization},
number = {4},
pages = {504--524},
title = {{Spatial, Temporal and Spatio-Temporal Patterns of Maritime Piracy}},
url = {http://jrc.sagepub.com/cgi/doi/10.1177/0022427812469113},
volume = {50},
year = {2013}
}
@article{Wang2013a,
abstract = {Many crimes can happen every day in a major city, and fig-uring out which ones are committed by the same individualor group is an important and dicult data mining challenge.To do this, we propose a pattern detection algorithm calledSeries Finder, that grows a pattern of discovered crimes fromwithin a database, starting from a “seed” of a few crimes. Se-ries Finder incorporates both the common characteristics ofall patterns and the unique aspects of each specific pattern.We compared Series Finder with classic clustering and clas-sification models applied to crime analysis. It has promisingresults on a decade’s worth of crime pattern data from theCambridge Police Department.},
author = {Wang, Tong and Rudin, Cynthia and Wagner, Daniel and Sevieri, Rich},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Wang et al.{\_}2013{\_}Detecting Patterns of Crime with Series Finder.pdf:pdf},
isbn = {9781577356288},
journal = {AAAI (Late-Breaking Developments) '13},
keywords = {AAAI Technical Report WS-13-17},
pages = {140--142},
title = {{Detecting Patterns of Crime with Series Finder.}},
url = {http://web.mit.edu/rudin/www/WangRuWaSeAAAI13.pdf},
year = {2013}
}
@article{Kaluza2010,
abstract = {Transportation networks play a crucial role in human mobility, the exchange of goods, and the spread of invasive species. With 90{\%} of world trade carried by sea, the global network of merchant ships provides one of the most important modes of transportation. Here we use information about the itineraries of 16,363 cargo ships during the year 2007 to construct a network of links between ports. We show that the network has several features which set it apart from other transportation networks. In particular, most ships can be classified in three categories: bulk dry carriers, container ships and oil tankers. These three categories do not only differ in the ships' physical characteristics, but also in their mobility patterns and networks. Container ships follow regularly repeating paths whereas bulk dry carriers and oil tankers move less predictably between ports. The network of all ship movements possesses a heavy-tailed distribution for the connectivity of ports and for the loads transported on the links with systematic differences between ship types. The data analyzed in this paper improve current assumptions based on gravity models of ship movements, an important step towards understanding patterns of global trade and bioinvasion.},
archivePrefix = {arXiv},
arxivId = {1001.2172},
author = {Kaluza, Pablo and K{\"{o}}lzsch, Andrea and Gastner, Michael T. and Blasius, Bernd},
eprint = {1001.2172},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Kaluza et al.{\_}2010{\_}The complex network of global cargo ship movements(2).pdf:pdf},
keywords = {bioinvasion,cargo ships,complex network,transportation},
title = {{The complex network of global cargo ship movements}},
url = {http://arxiv.org/abs/1001.2172},
year = {2010}
}
@article{Grover2007,
abstract = {Police analysts are required to unravel the complexities in data to assist operational personnel in arresting offenders and directing crime prevention strategies. However, the volume of crime that is being committed and the awareness of modern criminals make this a daunting task. The ability to analyse this amount of data with its inherent complexities without using computational support puts a strain on human resources. This paper examines the current techniques that are used to predict crime and criminality. Over time, these techniques have been refined and have achieved limited success. They are concentrated into three categories: statistical methods, these mainly relate to the journey to crime, age of offending and offending behaviour; techniques using geographical information systems that identify crime hot spots, repeat victimisation, crime attractors and crime generators; a miscellaneous group which includes machine learning techniques to identify patterns in criminal behaviour and studies involving re- offending. The majority of current techniques involve the prediction of either a single offender's criminality or a single crime type's next offence. These results are of only limited use in practical policing. It is our contention that Knowledge Discovery in Databases should be used on all crime types together with offender data, as a whole, to predict crime and criminality within a small geographical area of a police force.},
author = {Grover, Vikas and Adderley, Richard and Bramer, Max},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Grover, Adderley, Bramer{\_}2007{\_}Review of current crime prediction techniques.pdf:pdf},
isbn = {1-84628-665-4},
journal = {Applications and innovations in intelligent systems XIV},
pages = {233--237},
title = {{Review of current crime prediction techniques}},
volume = {c},
year = {2007}
}
@misc{Granovetter1973,
abstract = {Analysis of social networks is suggested as a tool for linking micro and macro levels of sociological theory. The procedure is illustrated by elaboration of the macro implications of one aspect of small-scale interaction: the strength of dyadic ties. It is argued that the degree of overlap of two individuals' friendship networks varies directly with the strength of their tie to one another. The impact of this principle on diffusion of influence and information, mobility opportunity, and community organization is explored. Stress is laid on the cohesive power of weak ties. Most network models deal, implicitly, with strong ties, thus confining their applicability to small, well-defined groups. Emphasis on weak ties lends itself to discussion of relations between groups and to analysis of segments of social structure not easily defined in terms of primary groups.},
author = {Granovetter, Mark S.},
booktitle = {American Journal of Sociology},
number = {6},
pages = {1360},
title = {{The Strength of Weak Ties}},
volume = {78},
year = {1973}
}
@article{Twyman-Ghoshal2014,
author = {Twyman-Ghoshal, Anamika a. and Pierce, Glenn},
doi = {10.1093/bjc/azu019},
file = {:E$\backslash$:/bjoer/Documents/Mendeley/Twyman-Ghoshal, Pierce{\_}2014{\_}The Changing Nature of Contemporary Maritime Piracy.pdf:pdf},
issn = {0007-0955},
journal = {British Journal of Criminology},
keywords = {contemporary maritime piracy database,maritime piracy,somalia},
number = {4},
pages = {652--672},
title = {{The Changing Nature of Contemporary Maritime Piracy}},
url = {http://bjc.oxfordjournals.org/lookup/doi/10.1093/bjc/azu019},
volume = {54},
year = {2014}
}