The swift rise of digitization in legal documentation has opened doors for artificial intelligence to revolutionize various tasks within the legal domain. Among these tasks is the segmentation of ...legal documents using rhetorical labels. This process, known as rhetorical role labeling, involves assigning labels (such as Final Judgment, Argument, Fact, etc.) to sentences within a legal case document. This task can be down streamed to various major legal analytics problems such as summarization of legal documents, readability of lengthy case documents, document similarity estimation, etc. The mentioned task of semantic segmentation of documents via labels is challenging as the legal documents are lengthy, unstructured and the labels are subjective in nature. Various previous works on automatic rhetorical role labeling was carried out using methods like conditional random fields with handcrafted features, etc. This research focuses on analyzing case documents from two different legal systems: the High Court of Kerala and the High Court of Justice in the United Kingdom. Through rigorous experimentation with a range of deep learning models, this study highlights the robustness and efficacy of deep learning methods in accurately labeling rhetorical roles within legal texts. Additionally, comprehensive annotation of legal case documents from the UK and analysis of inter-annotator agreement are conducted. The overarching objective of this research is to design systems that facilitate a deeper comprehension of the organizational structure inherent in legal case documents.
In recent years, machine learning algorithms and in particular deep learning has shown promising results when used in the field of legal domain. The legal field is strongly affected by the problem of ...information overload, due to the large amount of legal material stored in textual form. Legal text processing is essential in the legal domain to analyze the texts of the court events to automatically predict smart decisions. With an increasing number of digitally available documents, legal text processing is essential to analyze documents which helps to automate various legal domain tasks. Legal document classification is a valuable tool in legal services for enhancing the quality and efficiency of legal document review. In this paper, we propose Sammon Keyword Mapping-based Quadratic Discriminant Recurrent Multilayer Perceptive Deep Neural Classifier (SKM-QDRMPDNC), a system that applies deep neural methods to the problem of legal document classification. The SKM-QDRMPDNC technique consists of many layers to perform the keyword extraction and classification. First, the set of legal documents are collected from the dataset. Then the keyword extraction is performed using Sammon Mapping technique based on the distance measure. With the extracted features, Quadratic Discriminant analysis is applied to perform the document classification based on the likelihood ratio test. Finally, the classified legal documents are obtained at the output layer. This process is repeated until minimum error is attained. The experimental assessment is carried out using various performance metrics such as accuracy, precision, recall, F-measure, and computational time based on several legal documents collected from the dataset. The observed results validated that the proposed SKM-QDRMPDNC technique provides improved performance in terms of achieving higher accuracy, precision, recall, and F-measure with minimum computation time when compared to existing methods.
Everyone is making constant efforts to establish an effective diagnostic approach, therapy and control of the spread of the pandemic. Due to a flexible formulation, the parameters prior to the normal ...distributions and explicitly formulate assumptions on the transition probabilities between these categories over time. The spread of the COVID-19 pandemic represents a serious threat for scientists and academics, health professionals and even governments today. The Hospital wards are classified into Intensive Care Unit (ICU), Regular Wards (RW) with Recovered (R) and Deceased (D).. The formulation may be truncated to include particular hypotheses with an epidemiological interpretation. The principles of Three-Way Decision Theory could be used to anticipate and diagnose COVID-19 patients were classified into one of three zones based on their symptoms: Positive, Negative, or Boundary, and treatment are recommended if necessary. The thresholds that distinguish the three zones are determined using a variance-based criterion. Examine the impact of nonpharmaceutical interventions and the findings from data gathered during the second wave of the pandemic in Trivandrum, India.The Three-Way Decision Theory model has a good fit and gives good predictive performance, especially for RW and ICU patients, according to suitable discrepancy metrics that were created to assess and compare models. 95 percent accuracy increased and calculated values for 10 days to demonstrate the temporal aspects of the expected daily reproduction number R
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The discovery of potent, bioavailable small molecule inhibitors of p53-HDM2 PPI led us to investigate subsequent modifications to address a CYP3A4 time-dependent inhibition liability. ...On the basis of the crystal structure of HDM2 in complex with 2, further functionalization of the solvent exposed area of the molecule that binds to Phe19 pocket were investigated as a strategy to modulate the molecule liphophilicity. Introduction of 2-oxo-nicotinic amide at Phe19 proved a viable strategy in obtaining inhibitors exempt from CYP3A4 time-dependent inhibition liability.
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Partition the sample space to the user requirement is an easy and efficient cluster method in many applications. Kmeans is one of the simple and efficient partition algorithms used in many cluster ...solutions. We suggest Multivariant Silhouette method to predict the cluster count value for Kmeans algorithm. The work proposes three new algorithms for initial seed selection. The Kmeans algorithm is modified using statistical measure Mean, Median, Partition centre for the cluster centroid calculation. In conventional Kmeans algorithm, the samples are compared with all the partition centroids to decide the inclusion of a sample in a cluster. In Kmeans9+ algorithm, the samples are compared only with the centroids of current and eight nearest neighbouring cluster partitions. It reduces the needless comparisons of samples with cluster centroids and improve the efficiency of the algorithm. The performance of created algorithms is evaluated using data from UCI and KBPE SSLC. Cluster efficiency analysis is done using the cluster evaluation indices such as Silhouette and Dunn Index. Nine nearest neighbour uniform partition cluster model Kmeans9+ improve the performance of the K means algorithm and obtain the natural cluster results with minimum iterations.
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PRATHALA TABLE of ALPHANUMERALS is a 62 x 62 matrix table developed by the authors for cryptographic purpose. In this paper a newly developed table of ALPHANUMERALS is proposed using Vigenere cipher ...logic. About (62!)62 tables can be generated. Each table is a 62 x 62 matrix. At any point of time any one of the tables can be used for encryption. The same table is to be regenerated and used for decryption. Experiments conducted shows that PRATHALA TABLE of ALPHANUMERALS method is much more secure than Vigenere Table Method.
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The discovery of 3,3-disubstituted piperidine 1 as novel p53-HDM2 inhibitors prompted us to implement subsequent SAR follow up directed towards piperidine core modifications. Conformational ...restrictions and further functionalization of the piperidine core were investigated as a strategy to gain additional interactions with HDM2. Substitutions at positions 4, 5 and 6 of the piperidine ring were explored. Although some substitutions were tolerated, no significant improvement in potency was observed compared to 1. Incorporation of an allyl side chain at position 2 provided a drastic improvement in binding potency.
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Cerium(IV) ammonium nitrate mediated reaction of sodium arene sulphinate and sodium iodide with alkenes afforded vinyl sulphones in very good yields.
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A highly efficient and practical route to 3,4-isopropylidene proline I, starting from (+)-3-carene, was developed. The three continuous stereocenters were constructed using the inherent chirality of ...the starting natural product 2. The overall yield for the 12-step synthesis is 34%. The optimized sequence leading to 1 has been successfully applied on a multigram scale, thereby establishing the practicality of this route.
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