Search

The paper presents different clustering approaches in legal judgments from the Special Civil Court located at the Federal University of Santa Catarina (JEC/UFSC). The subject is Consumer Law, specifically cases in which consumers claim moral and material compensation from airlines for service failures. To identify patterns from the dataset, we apply four types of clustering algorithms: Hierarchical and Lingo (soft clustering), K-means and Affinity Propagation (hard clustering). We evaluate the results based on the following criteria: (1) entropy and purity; (2) algorithm's ability in providing labels; (3) legal expert's evaluation; and (4) experimental complexity. The results demonstrate that the most advantageous approach is Hierarchical Clustering, since it has the best entropy and purity numbers, as well as the least difficulty for the expert to analyze the clusters, and the least experimental complexity. The main contribution of the paper is to show the advantages and disadvantages of each approach, especially to identify labels in unstructured and non-indexed legal texts. [ABSTRACT FROM AUTHOR]

The line notations of chemical structures are more compact than those of graphs and connection tables, so they can be useful for storing and transferring a large number of molecular structures. The simplified molecular input line system (SMILES) representation is the most extensively used, as it is much easier to utilise and comprehend than others, and it can be generated automatically from connection tables. A SMILES represents and encodes the molecule structure. It has been used by an existing method, LINGO, to calculate the molecular similarities and predict the structure-related properties. The LINGO method decomposes a canonical SMILES into a set of substrings of four characters referred to as LINGOs. The purpose of LINGO method is to measure the similarity between a pair of molecules by comparing the LINGOs that occur in each molecule. This paper aims to introduce an alternative version of the LINGO method using LINGOs of different lengths, called LINGO-DL. LINGO-DL is based on the fragmentation of canonical SMILES into substrings of three different lengths rather than one in LINGO method. Retrospective virtual screening experiments with MDDR, DUD, and MUV datasets show that the LINGO-DL outperforms the LINGO method, especially when the active molecules being sought have a high degree of structural heterogeneity. [ABSTRACT FROM AUTHOR]

Background: Solid Waste Management (SWM) in metropolises with systematic methods and following environmental issues, is one of the most important subjects in the area of urban management. In this regard, it is regarded as a legal entity so that its activities are not overshadowed by other urban activities. In this paper, a linear mathematical programming model has been designed for integrated SWM. Using Lingo software and required data from Tehran, the proposed model has been applied for Tehran SWM system as a case study. Results: To determine the optimal status of the available system for Tehran's Solid Waste Management System (SWMS), a novel linear programming model is applied. Tehran has 22 municipal regions with 11 transfer stations and 10 processing units. By running of the model, the transfer stations and processing units are decreased to 10 and 6 units, respectively. Conclusions: The proposed model is an alternative method for improvement the SWMS by decreasing the transfer stations and processing units. [ABSTRACT FROM AUTHOR]

Paddy fields not only serve to produce food but also have a variety of important ecological functions. Apart from the internal benefit (i.e., crop production), there are external benefits (i.e., reduction of greenhouse gases, oxygen generation, reduction of biological oxygen demand, flood mitigation, and other functions that are difficult to quantify). In the present study, the optimal fallow locations and areas were determined for evaluating the multifunctional benefits of paddy fields during drought periods, by using an optimization model for fallow fields under different exceedance probabilities of river inflows. For each time step, the appropriate probability distributions for river inflows to the Chi-Chi Weir (range 50-90 %) for generating system inflows were obtained. The optimization model for fallow fields was solved using Lingo. It was observed that the external benefits of paddy fields accounted for 76 % of total benefits, with the production benefit accounting for the remainder. The total benefits decreased as the exceedance probability of river discharges increased. Our findings indicate that fallow areas increase as irrigation areas shift downstream. [ABSTRACT FROM AUTHOR]