Subclass problem-dependent design for error-correcting output codes

A common way to model multiclass classification problems is by means of Error-Correcting Output Codes (ECOCs). Given a multiclass problem, the ECOC technique designs a code word for each class, where each position of the code identifies the membership of the class for a given binary problem. A classification decision is obtained by assigning the label of the class with the closest code. One of the main requirements of the ECOC design is that the base classifier is capable of splitting each subgroup of classes from each binary problem. However, we cannot guarantee that a linear classifier model convex regions. Furthermore, nonlinear classifiers also fail to manage some type of surfaces. In this paper, we present a novel strategy to model multiclass classification problems using subclass information in the ECOC framework. Complex problems are solved by splitting the original set of classes into subclasses and embedding the binary problems in a problem-dependent ECOC design. Experimental results show that the proposed splitting procedure yields a better performance when the class overlap or the distribution of the training objects conceal the decision boundaries for the base classifier. The results are even more significant when one has a sufficiently large training size.

A model of multilingual digital library

This paper addresses the problem of multilingual digital libraries. The motivation for a such a digital library comes from the diversity of languages of the Internet users as well as the diversity of content authors, from e-book authors to writers of courseware. The basic definitions of such a system, the specifications of its functionality and the identification of the items it holds are discussed. The impact of multilinguism in each of the former aspects is presented. A case study of a multilingual digital library - in the Maxwell System in PUC-Rio - is described in the last sections. Its main characteristics are described and the current status of its digital library is shown.

Computer-Aided Business Model Design

There is a lack of dedicated tools for business model design at a strategic level. However, in today's economic world the need to be able to quickly reinvent a company's business model is essential to stay competitive. This research focused on identifying the functionalities that are necessary in a computer-aided design (CAD) tool for the design of business models in a strategic context. Using design science research methodology a series of techniques and prototypes have been designed and evaluated to offer solutions to the problem. The work is a collection of articles which can be grouped into three parts: First establishing the context of how the Business Model Canvas (BMC) is used to design business models and explore the way in which CAD can contribute to the design activity. The second part extends on this by proposing new technics and tools which support elicitation, evaluation (assessment) and evolution of business models design with CAD. This includes features such as multi-color tagging to easily connect elements, rules to validate coherence of business models and features that are adapted to the correct business model proficiency level of its users. A new way to describe and visualize multiple versions of a business model and thereby help in addressing the business model as a dynamic object was also researched. The third part explores extensions to the business model canvas such as an intermediary model which helps IT alignment by connecting business model and enterprise architecture. And a business model pattern for privacy in a mobile environment, using privacy as a key value proposition. The prototyped techniques and proposition for using CAD tools in business model modeling will allow commercial CAD developers to create tools that are better suited to the needs of practitioners.

Susceptibility of clinical isolates of Leishmania aethiopica to miltefosine, paromomycin, amphotericin B and sodium stibogluconate using amastigote-macrophage in vitro model.

Cutaneous Leishmaniasis (CL) caused by Leishmania aethiopica is a public health and social problem with a sequel of severe and mutilating skin lesions. It is manifested in three forms: localized CL (LCL), mucosal CL (MCL) and diffuse CL (DCL). Unresponsiveness to sodium stibogluconate (Sb(V)) is common in Ethiopian CL patients. Using the amastigote-macrophage in vitro model the susceptibility of 24 clinical isolates of L. aethiopica derived from untreated patients was investigated. Eight strains of LCL, 9 of MCL, and 7 of DCL patients together with a reference strain (MHOM/ET/82/117/82) were tested against four antileishmanial drugs: amphotericin B, miltefosine, Sb(V) and paromomycin. In the same order of drugs, IC(50) (μg/ml±SD) values for the 24 strains tested were 0.16±0.18, 5.88±4.79, 10.23±8.12, and 13.63±18.74. The susceptibility threshold of isolates originating from the 3 categories of patients to all 4 drugs was not different (p>0.05). Maximal efficacy was superior for miltefosine across all the strains. Further susceptibility test could validate miltefosine as a potential alternative drug in cases of sodium stibogluconate treatment failure in CL patients.

A Generalized Model Study of Scour Around Bridge Piers and Abutments, HR-24, 1953

Four classes of variables are apparent in the problem of scour around bridge piers and abutments--geometry of piers and abutments, stream-flow characteristics, sediment characteristics, and geometry of site. The laboratory investigation, from its inception, has been divided into four phases based on these classes. In each phase the variables in three of the classes are held constant and those in the pertinent class are varied. To date, the first three phases have been studied. Typical scour bole patterns related to the geometry of the pier or abutment have been found. For equilibrium conditions of scour with uniform sand, the velocity of flow and the sand size do not appear to have any measurable effects on the depth of scour. This result is especially encouraging in the search for correlation between model and prototype since it would indicate that, primarily, only the depth of flow might be involved in the scale effect. The technique of model testing has been simplified, therefore, because rate of sediment transportation does not need to be scaled. Prior to the establishment of equilibrium conditions, however, depths of scour in excess of those for equilibrium conditions have been found. A concept of active scour as an imbalance between sediment transport capacity and rate of sediment supply has been used to explain the laboratory observations.

Update on the non-prewhitening model observer in computed tomography for the assessment of the adaptive statistical and model-based iterative reconstruction algorithms.

The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.

Development of a Subgrade Drainage Model for Unpaved Roads, TR-654, 2015

With over 68 thousand miles of gravel roads in Iowa and the importance of these roads within the farm-to-market transportation system, proper water management becomes critical for maintaining the integrity of the roadway materials. However, the build-up of water within the aggregate subbase can lead to frost boils and ultimately potholes forming at the road surface. The aggregate subbase and subgrade soils under these gravel roads are produced with material opportunistically chosen from local sources near the site and, many times, the compositions of these sublayers are far from ideal in terms of proper water drainage with the full effects of this shortcut not being fully understood. The primary objective of this project was to provide a physically-based model for evaluating the drainability of potential subbase and subgrade materials for gravel roads in Iowa. The Richards equation provided the appropriate framework to study the transient unsaturated flow that usually occurs through the subbase and subgrade of a gravel road. From which, we identified that the saturated hydraulic conductivity, Ks, was a key parameter driving the time to drain of subgrade soils found in Iowa, thus being a good proxy variable for accessing roadway drainability. Using Ks, derived from soil texture, we were able to identify potential problem areas in terms of roadway drainage . It was found that there is a threshold for Ks of 15 cm/day that determines if the roadway will drain efficiently, based on the requirement that the time to drain, Td, the surface roadway layer does not exceed a 2-hr limit. Two of the three highest abundant textures (loam and silty clay loam), which cover nearly 60% of the state of Iowa, were found to have average Td values greater than the 2-hr limit. With such a large percentage of the state at risk for the formation of boils due to the soil with relatively low saturated hydraulic conductivity values, it seems pertinent that we propose alternative design and/or maintenance practices to limit the expensive repair work in Iowa. The addition of drain tiles or French mattresses my help address drainage problems. However, before pursuing this recommendation, a comprehensive cost-benefit analysis is needed.

Bayesian Networks and the Value of the Evidence for the Forensic Two-Trace Transfer Problem

Forensic scientists face increasingly complex inference problems for evaluating likelihood ratios (LRs) for an appropriate pair of propositions. Up to now, scientists and statisticians have derived LR formulae using an algebraic approach. However, this approach reaches its limits when addressing cases with an increasing number of variables and dependence relationships between these variables. In this study, we suggest using a graphical approach, based on the construction of Bayesian networks (BNs). We first construct a BN that captures the problem, and then deduce the expression for calculating the LR from this model to compare it with existing LR formulae. We illustrate this idea by applying it to the evaluation of an activity level LR in the context of the two-trace transfer problem. Our approach allows us to relax assumptions made in previous LR developments, produce a new LR formula for the two-trace transfer problem and generalize this scenario to n traces.

Reaction-diffusion lattice gas: Theory and computer results

We report on the study of nonequilibrium ordering in the reaction-diffusion lattice gas. It is a kinetic model that relaxes towards steady states under the simultaneous competition of a thermally activated creation-annihilation $(reaction$) process at temperature T, and a diffusion process driven by a heat bath at temperature T?T. The phase diagram as one varies T and T, the system dimension d, the relative priori probabilities for the two processes, and their dynamical rates is investigated. We compare mean-field theory, new Monte Carlo data, and known exact results for some limiting cases. In particular, no evidence of Landau critical behavior is found numerically when d=2 for Metropolis rates but Onsager critical points and a variety of first-order phase transitions.

Ising critical behavior of a non-Halmiltonian lattice system

We study steady states in d-dimensional lattice systems that evolve in time by a probabilistic majority rule, which corresponds to the zero-temperature limit of a system with conflicting dynamics. The rule satisfies detailed balance for d=1 but not for d>1. We find numerically nonequilibrium critical points of the Ising class for d=2 and 3.

Genetic algorithm for sequencing in midex model non-permutation flowshops using constrained buffers

Este trabajo presenta un Algoritmo Genético (GA) del problema de secuenciar unidades en una línea de producción. Se tiene en cuenta la posibilidad de cambiar la secuencia de piezas mediante estaciones con acceso a un almacén intermedio o centralizado. El acceso al almacén además está restringido, debido al tamaño de las piezas.AbstractThis paper presents a Genetic Algorithm (GA) for the problem of sequencing in a mixed model non-permutation flowshop. Resequencingis permitted where stations have access to intermittent or centralized resequencing buffers. The access to a buffer is restricted by the number of available buffer places and the physical size of the products.

Timing of Capacity Change: Models for Capital Intensive Industry

The suitable timing of capacity investments is a remarkable issue especially in capital intensive industries. Despite its importance, fairly few studies have been published on the topic. In the present study models for the timing of capacity change in capital intensive industry are developed. The study considers mainly the optimal timing of single capacity changes. The review of earlier research describes connections between cost, capacity and timing literature, and empirical examples are used to describe the starting point of the study and to test the developed models. The study includes four models, which describe the timing question from different perspectives. The first model, which minimizes unit costs, has been built for capacity expansion and replacement situations. It is shown that the optimal timing of an investment can be presented with the capacity and cost advantage ratios. After the unit cost minimization model the view is extended to the direction of profit maximization. The second model states that early investments are preferable if the change of fixed costs is small compared to the change of the contribution margin. The third model is a numerical discounted cash flow model, which emphasizes the roles of start-up time, capacity utilization rate and value of waiting as drivers of the profitable timing of a project. The last model expands the view from project level to company level and connects the flexibility of assets and cost structures to the timing problem. The main results of the research are the solutions of the models and analysis or simulations done with the models. The relevance and applicability of the results are verified by evaluating the logic of the models and by numerical cases.

On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation

In this paper, the theory of hidden Markov models (HMM) isapplied to the problem of blind (without training sequences) channel estimationand data detection. Within a HMM framework, the Baum–Welch(BW) identification algorithm is frequently used to find out maximum-likelihood (ML) estimates of the corresponding model. However, such a procedureassumes the model (i.e., the channel response) to be static throughoutthe observation sequence. By means of introducing a parametric model fortime-varying channel responses, a version of the algorithm, which is moreappropriate for mobile channels [time-dependent Baum-Welch (TDBW)] isderived. Aiming to compare algorithm behavior, a set of computer simulationsfor a GSM scenario is provided. Results indicate that, in comparisonto other Baum–Welch (BW) versions of the algorithm, the TDBW approachattains a remarkable enhancement in performance. For that purpose, onlya moderate increase in computational complexity is needed.

Toward a novel forensic intelligence model: systematic profiling of false identity documents

False identity documents represent a serious threat through their production and use in organized crime and by terrorist organizations. The present-day fight against this criminal problem and threats to national security does not appropriately address the organized nature of this criminal activity, treating each fraudulent document on its own during investigation and the judicial process, which causes linkage blindness and restrains the analysis capacity. Given the drawbacks of this case-by-case approach, this article proposes an original model in which false identity documents are used to inform a systematic forensic intelligence process. The process aims to detect links, patterns, and tendencies among false identity documents in order to support strategic and tactical decision making, thus sustaining a proactive intelligence-led approach to fighting identity document fraud and the associated organized criminality. This article formalizes both the model and the process, using practical applications to illustrate its powerful capabilities. This model has a general application and can be transposed to other fields of forensic science facing similar difficulties.

Forensic intelligence framework-Part I: induction of a transversal model by comparing illicit drugs and false identity documents monitoring

Forensic intelligence is a distinct dimension of forensic science. Forensic intelligence processes have mostly been developed to address either a specific type of trace or a specific problem. Even though these empirical developments have led to successes, they are trace-specific in nature and contribute to the generation of silos which hamper the establishment of a more general and transversal model. Forensic intelligence has shown some important perspectives but more general developments are required to address persistent challenges. This will ensure the progress of the discipline as well as its widespread implementation in the future. This paper demonstrates that the description of forensic intelligence processes, their architectures, and the methods for building them can, at a certain level, be abstracted from the type of traces considered. A comparative analysis is made between two forensic intelligence approaches developed independently in Australia and in Europe regarding the monitoring of apparently very different kind of problems: illicit drugs and false identity documents. An inductive effort is pursued to identify similarities and to outline a general model. Besides breaking barriers between apparently separate fields of study in forensic science and intelligence, this transversal model would assist in defining forensic intelligence, its role and place in policing, and in identifying its contributions and limitations. The model will facilitate the paradigm shift from the current case-by-case reactive attitude towards a proactive approach by serving as a guideline for the use of forensic case data in an intelligence-led perspective. A follow-up article will specifically address issues related to comparison processes, decision points and organisational issues regarding forensic intelligence (part II).