Small Number Of States Research Articles

Prison health as public health in Afghanistan? A policy analysis of the on-going reform process

Our knowledge about prisoners’ health in developing countries is patchy. Even in affluent societies the state of prisoners’ health leaves a lot to be desired. Significant progress in health care provision has been made in a small number of states or regions that entrust, instead of the detaining authority, the health authority with providing health care for prisoners. The Swiss canton of Geneva was a pioneer in making prison health completely independent from the prison administration in a process that started in the mid1980s. Norway, France, England, Wales and parts of Australia are recent examples that are best documented. Overlooked so far is the recent very similar experience in one of the world’s poorest and most war-affected countries: Afghanistan. This article describes the progress reform has made and the challenges it is facing in that particular context. The article is the result of two visits to Afghanistan: an external evaluation commissioned by the European Union (EU) was conducted between 13 and 25 October 2012; the methodology consisted of a literature and document study, three prison visits and interviews (n1⁄4 49) with representatives

Benefits of a Department of Corrections Partnership With a Health Sciences University

More than half of the state prisons in the United States outsource health care. While most states contract with private companies, a small number of states have reached out to their health science universities to meet their needs for health care of prisoners. New Jersey is the most recent state to form such an agreement. This article discusses the benefits of such a model for New Jersey's Department of Corrections and for New Jersey's health sciences university, the Rutgers University, formerly the University of Medicine and Dentistry of New Jersey. The benefits for both institutions should encourage other states to participate in such affiliations.

Cognitively inspired reinforcement learning architecture and its application to giant-swing motion control

Many algorithms and methods in artificial intelligence or machine learning were inspired by human cognition. As a mechanism to handle the exploration–exploitation dilemma in reinforcement learning, the loosely symmetric (LS) value function that models causal intuition of humans was proposed (Shinohara et al., 2007). While LS shows the highest correlation with causal induction by humans, it has been reported that it effectively works in multi-armed bandit problems that form the simplest class of tasks representing the dilemma. However, the scope of application of LS was limited to the reinforcement learning problems that have K actions with only one state (K-armed bandit problems). This study proposes LS-Q learning architecture that can deal with general reinforcement learning tasks with multiple states and delayed reward. We tested the learning performance of the new architecture in giant-swing robot motion learning, where uncertainty and unknown-ness of the environment is huge. In the test, the help of ready-made internal models or functional approximation of the state space were not given. The simulations showed that while the ordinary Q-learning agent does not reach giant-swing motion because of stagnant loops (local optima with low rewards), LS-Q escapes such loops and acquires giant-swing. It is confirmed that the smaller number of states is, in other words, the more coarse-grained the division of states and the more incomplete the state observation is, the better LS-Q performs in comparison with Q-learning. We also showed that the high performance of LS-Q depends comparatively little on parameter tuning and learning time. This suggests that the proposed method inspired by human cognition works adaptively in real environments.

A low-complexity maximum likelihood decoder for tail-biting trellis

Abstract Tail-biting trellises are defined on a circular time axis and can have a smaller number of states than equivalent conventional trellises. Existing circular Viterbi algorithms (CVAs) on the tail-biting trellis are non-convergent and sub-optimal. In this study, we show that the net path metric of each tail-biting path is lower-bounded during the decoding process of the CVA. This property can be applied to remove unnecessary iterations of the CVA and results in a convergent maximum likelihood (ML) decoder. Simulation results show that the proposed algorithm exhibits higher decoding efficiency compared with other existing ML decoders.

Turbo Charged Local Stochastic Volatility Models

This article presents an alternative formulation of the standard Local Stochastic Volatility model (LSV) widely used for the pricing and risk-management of FX derivatives and to a lesser extent of equity derivatives. In the standard model, calibration is achieved by solving a non-linear two-factor Kolmogorov forward PDE, where a minimum number of vol points is required to achieve convergence of a finite difference implementation. In contrast, we propose to model the volatility process by a Markov chain defined over an arbitrary small number of states, so that calibration and pricing are achieved by solving a coupled system of one-factor PDEs. The practical benefits are twofolds: existing one-factor PDE solvers can be recycled to model stochastic volatility, while the reduction in number of discretisation points implies a speedup in execution time that enables real-time risk-management of large derivatives position.

Small States Foreign Policy: The Case of Kosovo

Enormous changes have occurred in international system in the last twenty years. As a result, the number of Small States in international system has grown rapidly. These processes have had strong and noticeable impact in the foreign policy of all states, particularly in the foreign policy of small states. This paper examines Kosovo’s foreign policy behavior as an independent state. By conducting an in depth analysis in this case study, paper attempts to clarify which are the main dominant sources that influence more the Kosovo’s foreign policy behavior. Foreign policy of Kosovo as a small state was characterized by two main behaviors: tendency to secure multinational agreements and join multinational institutions and the tendency to rely on larger states, especially on USA, in order to ensure protection, partnership and resources. The main variables which have proved to have significant impact in Kosovo’s foreign policy behavior are systemic variables: a category which is based mainly in nonhuman aspects of a society’s external environment or in any kind of action occurring abroad and influencing the choices made by officials. DOI: 10.5901/mjss.2013.v4n2p287

Methodology for calculating the impact of distributed generation on energy losses in a distribution network

This paper is the result of the Master's final project 'Methodology for calculating the impact of distributed generation on energy losses in distribution network'. The question is whether, for estimation of the impact of the power plant on energy losses in the distribution network, it is necessary to analyze each hour value of small power plant engagement and its effect, or it is sufficient to analyze a small number of states, and the extent to which it is possible to reduce the number of states that will be analyzed in order to review adequately the impact of the power plant on the change of energy losses in the network. To answer this question, an algorithm consisting of two steps is performed, annual production diagrams are obtained and, on the basis of calculated specific discrete values, the impact of the small power plant on energy losses in the distribution network to which it is connected is evaluated.

Evaluation and Optimization of Discrete State Models of Protein Folding

The space accessed by a folding macromolecule is vast, and how to best project computer simulations of protein folding trajectories into an interpretable sequence of discrete states is an open research problem. There are numerous alternative ways of associating individual configurations into collective states, and in deciding on the number of such clustered states there is a trade-off between human interpretability (smaller number of states) and accuracy of representation (larger number of states). Here we introduce a trajectory likelihood measure for assessing alternative discrete state models of protein folding. We find that widely used rmsd-based clustering methods require large numbers of initial states and a second agglomeration step based on kinetic connectivity to produce models with high predictive power; this is the approach taken in elegant recent work with Markov State Models of protein folding. In contrast, we find that grouping of states based on secondary structure pairings or contact maps, when refined with K-means clustering, yields higher likelihood models with many fewer states. Using the most predictive contact map representation to study the folding transitions of the WW domain in very long molecular dynamics simulations, we identify new states and transitions. The methods should be generally useful for investigating the structural transitions in protein folding simulations for larger proteins.

Markov chain inversion approach to identify the transition rates of ion channels

We consider how to identify the transition rates of ion channels with the underlying scheme which is kinetically modelled as time-homogeneous Markov chain. A Markov chain inversion approach is developed to perform a difficult inversion to identify the transition rates from the parameters characterizing the lifetime distributions at a small number of states, although it is straightforward to derive the lifetime distribution. The general explicit equations relating the parameters of the lifetime distribution to the transition rates are derived and transition rates are then obtained as roots to this system of equations. The concrete solutions are proposed to the basic and regular schemes such as linear, star-graph branch and loop. Useful conclusions and solutions to realistic schemes are also included to show its efficiency.

Exploring Discrete Dynamics.Andrew Wuensche. (2011, Luniver Press.) xxxvii + 498 pages, 290 figures, 31 tables.

<i>Exploring Discrete Dynamics.</i>Andrew Wuensche. (2011, Luniver Press.) xxxvii + 498 pages, 290 figures, 31 tables.

Germany's Dialogue with Strasbourg: Extrapolating theBundesverfassungsgericht'sRelationship with the European Court of Human Rights in the Preventive Detention Decision

Within the Council of Europe, the relationship between the ECtHR and the member states is crucial for the survival and effective functioning of the Court. The ECtHR is currently overwhelmed by applications, the bulk of which emanate from a relatively small number of states, notably Russia, Rumania, Turkey, and the Ukraine. The backlog of cases will soon be toppling the vertiginous mark of 160,000, the adjudication of which alone would take the Court more than six years. The sheer number of cases exemplifies the system's urgent need for reform. Lately, discussions have been heavily influenced by considerations of subsidiarity, which the earlier Interlaken Declaration-as well as the recent Brighton Conference-emphasized as the key for the future relationship between the ECtHR and member states. Discussions about the principle's proper role in the relationship between member states and the ECHR, however, are far from over. This is due to questions regarding the principle itself, as well as to the factual realities dominating in the ECtHR-national court relationship. The principle often focuses on a strict separation of competences at two different levels, the national and the international, and many understandings of that principle require that the two levels stand in a more or less hierarchical relationship. This is difficult to assume in the Council of Europe context, where, compared to the EU, neither the doctrine of direct effect nor the principle of primacy in application reigns. Moreover, Strasbourg's emphasis on subsidiarity appears to focus on the responsibility of the member states to remedy human rights violations. In line with that argument, scholars have opined that the ECHR system should focus on an approach in which the ECtHR would be involved only if there are good reasons to depart from interpretation at the national level. Nonetheless, others recently doubted the overall usefulness of such an understanding of subsidiarity, since those member states responsible for the lion's share of new applications to the ECHR often neither possess a functioning judiciary nor functioning judicial or executive institutions, in general.

Ultrametricity in Protein Folding Dynamics.

The free energy of the transition state (TS) between two nodes of an ergodic Markov state model (MSM) can be obtained from the minimum cut, which is the set of edges that has the smallest sum of the flow capacities among all the possible cuts separating the two nodes. Here, we first show that the free energy of the TS is an ultrametric distance. The ultrametric property offers a way to simplify the MSM in a small number of states and, as a consequence, meaningful rate constants (free energy barriers) for the simplified MSM can be defined. We also present a new definition of the cut-based free energy profile (cbFEP), which is useful to check for the existence of a state for which the equilibration is much faster than the time to escape from it. From our analysis, a parallelism emerges between the minimum cut (maximum flow), and transition state theory (TST) or Kramers' theory.

Multiple model target tracking with variable rate particle filters

Fixed rate state space models are the conventional models used to track the maneuvering objects. In contrast to fixed rate models, recently introduced variable rate particle filter (VRPF) is capable of tracking the target with a small number of states by imposing a Gamma distribution on the state arrival times while the object trajectory is approached by a single dynamic motion model. Using a single dynamic motion model limits the capability of estimating the characteristics of maneuvering and smooth regions of the trajectory. To overcome this weakness we introduce an adaptive tracking method which incorporates multiple model approach with the variable rate model structure. The proposed model referred to as multiple model variable rate particle filter (MM-VRPF) adaptively locates frequent state points to the maneuvering regions resulting in a much more accurate tracking while preserving the parsimonious representation for the smooth regions of the trajectory. This is achieved by including a mode variable into the conventional variable rate state vector that enables us to define different sojourn and motion parameters for each motion mode using the multiple model structure. Simulation results show that the proposed algorithm outperforms the conventional variable rate particle filter, fixed rate multiple model particle filter and interacting multiple model.

Small States Foreign Policy: the Case of Kosovo

Enormous changes have occurred in international system in the last twenty years. As a result, the number of Small States in international system has grown rapidly. These processes have had strong and noticeable impact in the foreign policy of all states, particularly in the foreign policy of small states. This paper examines Kosovo's foreign policy behavior as an independent state. By conducting an in depth analysis in this case study, paper attempts to clarify which are the main dominant sources that influence more the Kosovo's foreign policy behavior. Foreign policy of Kosovo as a small state was characterized by two main behaviors: tendency to secure multinational agreements and join multinational institutions and the tendency to rely on larger states, especially on USA, in order to ensure protection, partnership and resources. The main variables which have proved to have significant impact in Kosovo's foreign policy behavior are systemic variables: a category which is based mainly in nonhuman aspects of a society's external environment or in any kind of action occurring abroad and influencing the choices made by officials.

Integrating Probabilistic Reasoning and Statistical Quality Control Techniques for Fault Diagnosis in Hybrid Domains

Bayesian networks, which may be compiled to arithmetic circuits in the interest of speed and predictability, provide a probabilistic method for system fault diagnosis. Currently, there is a limitation in arithmetic circuits in that they can only represent discrete random variables, while important fault types such as drift and offset faults are continuous and induce continuous sensor data. In this paper, we investigate how to handle continuous behavior while using discrete random variables with a small number of states. Central in our approach is the novel integration of a method from statistical quality control, known as cumulative sum (CUSUM), with probabilistic reasoning using static arithmetic circuits compiled from static Bayesian networks. Experimentally, an arithmetic circuit model of the ADAPT Electrical Power System (EPS), a real- world EPS located at the NASA Ames Research Center, is considered. We report on the validation of this approach using PRODIAGNOSE, which had the best performance in three of four industrial track competitions at the International Workshop on Principles of Diagnosis in 2009 and 2010 (DXC-09 and DXC-10). We demonstrate that PRODIAGNOSE, augmented with the CUSUM technique, is successful in diagnosing faults that are small in magnitude (offset faults) or drift linearly from a nominal state (drift faults). In one of these experiments, detection accuracy dramatically improved when CUSUM was used, jumping from 46.15% (CUSUM disabled) to 92.31% (CUSUM enabled).

Simulating reversible Turing machines and cyclic tag systems by one-dimensional reversible cellular automata

In this paper, we investigate how 1-D reversible cellular automata (RCAs) can simulate reversible Turing machines (RTMs) and cyclic tag systems (CTSs). A CTS is a universal string rewriting system proposed by M. Cook. First, we show that for any m -state n -symbol RTM there is a 1-D 2-neighbor RCA with a number of states less than ( m + 2 n + 1 ) ( m + n + 1 ) that simulates it. It improves past results both in the number of states and in the neighborhood size. Second, we study the problem of finding a 1-D RCA with a small number of states that can simulate any CTS. So far, a 30-state RCA that can simulate any CTS and works on ultimately periodic infinite configurations has been given by K. Morita. Here, we show there is a 24-state 2-neighbor RCA with this property.

Reduced order modeling of nonlinear time periodic systems subjected to external periodic excitations

In this work, new methodologies for order reduction of nonlinear systems with periodic coefficients subjected to external periodic excitations are presented. The periodicity of the linear terms is assumed to be non-commensurate with the periodicity of forcing vector. The dynamical equations of motion are transformed using the Lyapunov–Floquet (L–F) transformation such that the linear parts of the resulting equations become time-invariant while the forcing and nonlinearity takes the form of quasiperiodic functions. The techniques proposed here construct a reduced order equivalent system by expressing the non-dominant states as time-varying functions of the dominant (master) states. This reduced order model preserves stability properties and is easier to analyze, simulate and control since it consists of relatively small number of states in comparison with the large scale system. Specifically, two methods are discussed to obtain the reduced order model. First approach is a straightforward application of linear method similar to the ‘Guyan reduction’. The second novel technique proposed here extends the concept of ‘ invariant manifolds’ for the forced problem to construct the fundamental solution. Order reduction approach based on this extended invariant manifold technique yields unique ‘ reducibility conditions’. If these ‘ reducibility conditions’ are satisfied only then an accurate order reduction via extended invariant manifold approach is possible. This approach not only yields accurate reduced order models using the fundamental solution but also explains the consequences of various ‘ primary’ and ‘ secondary resonances’ present in the system. One can also recover ‘ resonance conditions’ associated with the fundamental solution which could be obtained via perturbation techniques by assuming weak parametric excitation. This technique is capable of handling systems with strong parametric excitations subjected to periodic and quasi-periodic forcing. It is anticipated that these order reduction techniques will provide a useful tool in the analysis and control system design of large-scale parametrically excited nonlinear systems subjected to external periodic excitations.

Recent Developments to Promote Transparency and Public Participation in Investment Treaty Arbitration

In the past, concerns have been expressed about the secrecy of international treaty arbitration. This paper attempts to show how the investment treaty arbitration system has responded to these criticisms. It starts by reviewing the arguments in favour of transparency and what different forms transparency can take in the context of investment treaty arbitration. The paper then sketches out the main developments in relation to transparency and highlights key issues that still remain to be resolved. In conclusion it is noted that the extent of publicity and public participation in a particular arbitration will depend on the instrument under which the claim is being brought. Whilst a small number of states have sought to promote the transparency agenda in their investment treaties, much more could be done by the majority of states.

Preparing Teachers for Diversity: Examination of Teacher Certification and Program Accreditation Standards in the 50 States and Washington, DC

State departments of education can play an important role in preparing teachers for effectively teaching diverse learners in our schools through state policies and standards on teacher certification and teacher education program accreditation. We conducted a content analysis of state standards on teacher certification and program accreditation in the 50 states and the District of Columbia to understand the type and characteristics of diversity-related requirements. We found that while all states addressed diversity in their standards, the type and characteristics of requirements varied across the states. The diversity requirements are ambiguous in most states, and only a small number of states utilize a “social reconstructionist” approach that focuses on preparing teachers to identify social inequality and take an active role to achieve educational and social equity.

Effects of fractal gating of potassium channels on neuronal behaviours

The classical model of voltage-gated ion channels assumes that according to a Markov process ion channels switch among a small number of states without memory, but a bunch of experimental papers show that some ion channels exhibit significant memory effects, and this memory effects can take the form of kinetic rate constant that is fractal. Obviously the gating character of ion channels will affect generation and propagation of action potentials, furthermore, affect generation, coding and propagation of neural information. However, there is little previous research on this series of interesting issues. This paper investigates effects of fractal gating of potassium channel subunits switching from closed state to open state on neuronal behaviours. The obtained results show that fractal gating of potassium channel subunits switching from closed state to open state has important effects on neuronal behaviours, increases excitability, rest potential and spiking frequency of the neuronal membrane, and decreases threshold voltage and threshold injected current of the neuronal membrane. So fractal gating of potassium channel subunits switching from closed state to open state can improve the sensitivity of the neuronal membrane, and enlarge the encoded strength of neural information.