A National Portrait of Domestic Violence Courts

A growing number of criminal courts nationwide handle domestic violence cases on separate calendars, termed domestic violence courts. There are now 208 confirmed domestic violence courts across the U.S. (Center for Court Innovation 2009). More than 150 similar projects have been established internationally. Some domestic violence courts emerged in the context of the broader "problem-solving court" movement and share characteristics with other specialized courts, such as separate dockets and specially trained judges. However, the origins of domestic violence courts are also distinct, growing out of the increased attention afforded domestic violence matters by the justice system over the past 30 years. With funding from the National Institute of Justice, this study explores how criminal domestic violence courts have evolved, their rationale, and how their operations vary across the U.S. This study does not test whether domestic violence courts reduce recidivism, protect victims, or achieve other specific effects -- although we provide a thorough literature review on these points. Rather, our aim is to present a comprehensive national portrait of the field as it exists today, laying the groundwork for future information exchange and research

Hospital Cost Accounting: Saving Lives and Saving on Costs

Within an industry constantly pursuing accuracy, a cost accounting system that addresses the ongoing concerns of saving money and increasing efficiency is a must. Now more than ever, hospitals require reliable information to combat the conflicting relationship between an increase in spending on new instruments and specialized staff, but a decrease in funding. This project explores potential avenues to find a successful cost accounting method using past research, analysis of hospitals’ current environments, and expert opinions from hospital and healthcare personnel. Each hospital is different based on their environment, surrounding population, type of services provided, and personal demands. This study seeks to contribute to previous studies attempting to debunk the navigation process for each hospital looking to find their cost accounting perfect match and where sights should be set on in the future

Fast and Lean Immutable Multi-Maps on the JVM based on Heterogeneous Hash-Array Mapped Tries

An immutable multi-map is a many-to-many thread-friendly map data structure with expected fast insert and lookup operations. This data structure is used for applications processing graphs or many-to-many relations as applied in static analysis of object-oriented systems. When processing such big data sets the memory overhead of the data structure encoding itself is a memory usage bottleneck. Motivated by reuse and type-safety, libraries for Java, Scala and Clojure typically implement immutable multi-maps by nesting sets as the values with the keys of a trie map. Like this, based on our measurements the expected byte overhead for a sparse multi-map per stored entry adds up to around 65B, which renders it unfeasible to compute with effectively on the JVM. In this paper we propose a general framework for Hash-Array Mapped Tries on the JVM which can store type-heterogeneous keys and values: a Heterogeneous Hash-Array Mapped Trie (HHAMT). Among other applications, this allows for a highly efficient multi-map encoding by (a) not reserving space for empty value sets and (b) inlining the values of singleton sets while maintaining a (c) type-safe API. We detail the necessary encoding and optimizations to mitigate the overhead of storing and retrieving heterogeneous data in a hash-trie. Furthermore, we evaluate HHAMT specifically for the application to multi-maps, comparing them to state-of-the-art encodings of multi-maps in Java, Scala and Clojure. We isolate key differences using microbenchmarks and validate the resulting conclusions on a real world case in static analysis. The new encoding brings the per key-value storage overhead down to 30B: a 2x improvement. With additional inlining of primitive values it reaches a 4x improvement

Generalization Strategies for the Verification of Infinite State Systems

We present a method for the automated verification of temporal properties of infinite state systems. Our verification method is based on the specialization of constraint logic programs (CLP) and works in two phases: (1) in the first phase, a CLP specification of an infinite state system is specialized with respect to the initial state of the system and the temporal property to be verified, and (2) in the second phase, the specialized program is evaluated by using a bottom-up strategy. The effectiveness of the method strongly depends on the generalization strategy which is applied during the program specialization phase. We consider several generalization strategies obtained by combining techniques already known in the field of program analysis and program transformation, and we also introduce some new strategies. Then, through many verification experiments, we evaluate the effectiveness of the generalization strategies we have considered. Finally, we compare the implementation of our specialization-based verification method to other constraint-based model checking tools. The experimental results show that our method is competitive with the methods used by those other tools. To appear in Theory and Practice of Logic Programming (TPLP).Comment: 24 pages, 2 figures, 5 table

Natural resources conservation management and strategies in agriculture

This paper suggests a holistic framework for assessment and improvement of management strategies for conservation of natural resources in agriculture. First, it incorporates an interdisciplinary approach (combining Economics, Organization, Law, Sociology, Ecology, Technology, Behavioral and Political Sciences) and presents a modern framework for assessing environmental management and strategies in agriculture including: specification of specific “managerial needs” and spectrum of feasible governance modes (institutional environment; private, collective, market, and public modes) of natural resources conservation at different level of decision-making (individual, farm, eco-system, local, regional, national, transnational, and global); specification of critical socio-economic, natural, technological, behavioral etc. factors of managerial choice, and feasible spectrum of (private, collective, public, international) managerial strategies; assessment of efficiency of diverse management strategies in terms of their potential to protect diverse eco-rights and investments, assure socially desirable level of environmental protection and improvement, minimize overall (implementing, third-party, transaction etc.) costs, coordinate and stimulate eco-activities, meet preferences and reconcile conflicts of individuals etc. Second, it presents evolution and assesses the efficiency of diverse management forms and strategies for conservation of natural resources in Bulgarian agriculture during post-communist transformation and EU integration (institutional, market, private, and public), and evaluates the impacts of EU CAP on environmental sustainability of farms of different juridical type, size, specialization and location. Finally, it suggests recommendations for improvement of public policies, strategies and modes of intervention, and private and collective strategies and actions for effective environmental protection

Breaking Instance-Independent Symmetries In Exact Graph Coloring

Code optimization and high level synthesis can be posed as constraint satisfaction and optimization problems, such as graph coloring used in register allocation. Graph coloring is also used to model more traditional CSPs relevant to AI, such as planning, time-tabling and scheduling. Provably optimal solutions may be desirable for commercial and defense applications. Additionally, for applications such as register allocation and code optimization, naturally-occurring instances of graph coloring are often small and can be solved optimally. A recent wave of improvements in algorithms for Boolean satisfiability (SAT) and 0-1 Integer Linear Programming (ILP) suggests generic problem-reduction methods, rather than problem-specific heuristics, because (1) heuristics may be upset by new constraints, (2) heuristics tend to ignore structure, and (3) many relevant problems are provably inapproximable. Problem reductions often lead to highly symmetric SAT instances, and symmetries are known to slow down SAT solvers. In this work, we compare several avenues for symmetry breaking, in particular when certain kinds of symmetry are present in all generated instances. Our focus on reducing CSPs to SAT allows us to leverage recent dramatic improvement in SAT solvers and automatically benefit from future progress. We can use a variety of black-box SAT solvers without modifying their source code because our symmetry-breaking techniques are static, i.e., we detect symmetries and add symmetry breaking predicates (SBPs) during pre-processing. An important result of our work is that among the types of instance-independent SBPs we studied and their combinations, the simplest and least complete constructions are the most effective. Our experiments also clearly indicate that instance-independent symmetries should mostly be processed together with instance-specific symmetries rather than at the specification level, contrary to what has been suggested in the literature