MEASURING THE PERFORMANCE OF TWO-STAGE PRODUCTION SYSTEMS WITH SHARED INPUTS BY DATA ENVELOPMENT ANALYSIS

As a non-parametric technique in Operations Research and Economics, Data Envelopment Analysis (DEA) evaluates the relative efficiency of peer production systems or decision making units (DMUs) that have multiple inputs and outputs. In recent years, a great number of DEA studies have focused on two-stage production systems in series, where all outputs from the first stage are intermediate products that make up the inputs to the second stage. There are, of course, other types of two-stage processes that the inputs of the system can be freely allocated among two stages. For this type of two-stage production system, the conventional two-stage DEA models have some limitations e.g. efficiency formulation and linearizing transformation. In this paper, we introduce a relational DEA model, considering series relationship among two stages, to measure the overall efficiency of two-stage production systems with shared inputs. The linearity of DEA models is preserved in our model. The proposed DEA model not only evaluates the efficiency of the whole process, but also it provides the efficiency for each of the two sub-processes. A numerical example of US commercial banks from literature is used to clarify the model.Data envelopment analysis, Decision making unit, Two-stage, Shared input, Efficiency

Genetic algorithm for biobjective urban transit routing problem

This paper considers solving a biobjective urban transit routing problem with a genetic algorithm approach. The objectives are to minimize the passengers’ and operators’ costs where the quality of the route sets is evaluated by a set of parameters. The proposed algorithm employs an adding-node procedure which helps in converting an infeasible solution to a feasible solution. A simple yet effective route crossover operator is proposed by utilizing a set of feasibility criteria to reduce the possibility of producing an infeasible network. The computational results from Mandl’s benchmark problems are compared with other published results in the literature and the computational experiments show that the proposed algorithm performs better than the previous best published results in most cases

Managing Climatic Risks to Combat Land Degradation and Enhance Food security: Key Information Needs

This paper discusses the key information needs to reduce the negative impacts of weather variability and climate change on land degradation and food security, and identifies the opportunities and barriers between the information and services needed. It suggests that vulnerability assessments based on a livelihood concept that includes climate information and key socio-economic variables can overcome the narrow focus of common one-dimensional vulnerability studies. Both current and future climatic risks can be managed better if there is appropriate policy and institutional support together with technological interventions to address the complexities of multiple risks that agriculture has to face. This would require effective partnerships among agencies dealing with meteorological and hydrological services, agricultural research, land degradation and food security issues. In addition a state-of-the-art infrastructure to measure, record, store and disseminate data on weather variables, and access to weather and seasonal climate forecasts at desired spatial and temporal scales would be needed

Investigation of scaling properties of hysteresis in Finemet thin films

We study the behavior of hysteresis loops in Finemet Fe$_{73.5}$Cu$_1$Nb$_3$Si$_{18.5}$B$_4$ thin films by using a fluxometric setup based on a couple of well compensated pickup coils. The presence of scaling laws of the hysteresis area is investigated as a function of the amplitude and frequency of the applied field, considering sample thickness from about 20 nm to 5 $\mu$m. We do not observe any scaling predicted by theoretical models, while dynamic loops show a logarithmic dependence on the frequency.Comment: 2 pages, 2 figure

Extractive Chinese Spoken Document Summarization Using Probabilistic Ranking Models

Abstract. The purpose of extractive summarization is to automatically select indicative sentences, passages, or paragraphs from an original document according to a certain target summarization ratio, and then sequence them to form a concise summary. In this paper, in contrast to conventional approaches, our objective is to deal with the extractive summarization problem under a probabilistic modeling framework. We investigate the use of the hidden Markov model (HMM) for spoken document summarization, in which each sentence of a spoken document is treated as an HMM for generating the document, and the sentences are ranked and selected according to their likelihoods. In addition, the relevance model (RM) of each sentence, estimated from a contemporary text collection, is integrated with the HMM model to improve the representation of the sentence model. The experiments were performed on Chinese broadcast news compiled in Taiwan. The proposed approach achieves noticeable performance gains over conventional summarization approaches

Monopoles in the presence of the Chern-Simons term via the Julia-Toulouse approach

We study $QED_3$ with magnetic-like defects using the Julia-Toulouse condensation mechanism (JTM). By a careful treatment of the symmetries we suggest a geometrical interpretation for distinct debatable issues in the MCS-monopole system: (i) the induction of the non-conserved electric current together with the Chern-Simons term (CS), (ii) the deconfinement transition and, (iii) the computation of the fermionic determinant in the presence of Dirac string singularities. The JTM leads to proper interpretation of the non-conserved current as originating from Dirac brane symmetry breaking. The mechanism behind this symmetry breaking is clarified. The physical origin of the deconfinement transition becomes evident in the low energy effective theory induced by the JTM. The proper procedure to compute the fermionic determinant in the presence of Dirac branes will be presented. A byproduct of this approach is the possible appearance of statistical transmutation and the clarification for the different quantization rules for the topological mass.Comment: 6 pages, 2 figures, minor changes, references added, accepted for publication in Physics Letters

Long-Ranged Correlations in Sheared Fluids

The presence of long-ranged correlations in a fluid undergoing uniform shear flow is investigated. An exact relation between the density autocorrelation function and the density-mometum correlation function implies that the former must decay more rapidly than $1/r$, in contrast to predictions of simple mode coupling theory. Analytic and numerical evaluation of a non-perturbative mode-coupling model confirms a crossover from $1/r$ behavior at ''small'' $r$ to a stronger asymptotic power-law decay. The characteristic length scale is $\ell \approx \sqrt{\lambda_{0}/a}$ where $$ is the sound damping constant and $a$ is the shear rate.Comment: 15 pages, 2 figures. Submitted to PR