A novel Auto-ML Framework for Sarcasm Detection

Many domains have sarcasm or verbal irony presented in the text of reviews, tweets, comments, and dialog discussions. The purpose of this research is to classify sarcasm for multiple domains using the deep learning based AutoML framework. The proposed AutoML framework has five models in the model search pipeline, these five models are the combination of convolutional neural network (CNN), Long Short-Term Memory (LSTM), deep neural network (DNN), and Bidirectional Long Short-Term Memory (BiLSTM). The hybrid combination of CNN, LSTM, and DNN models are presented as CNN-LSTM-DNN, LSTM-DNN, BiLSTM-DNN, and CNN-BiLSTM-DNN. This work has proposed the algorithms that contrast polarities between terms and phrases, which are categorized into implicit and explicit incongruity categories. The incongruity and pragmatic features like punctuation, exclamation marks, and others integrated into the AutoML DeepConcat framework models. That integration was possible when the DeepConcat AutoML framework initiate a model search pipeline for five models to achieve better performance. Conceptually, DeepConcat means that model will integrate with generalized features. It was evident that the pretrain model BiLSTM achieved a better performance of 0.98 F1 when compared with the other five model performances. Similarly, the AutoML based BiLSTM-DNN model achieved the best performance of 0.98 F1, which is better than core approaches and existing state-of-the-art Tweeter tweet dataset, Amazon reviews, and dialog discussion comments. The proposed AutoML framework has compared performance metrics F1 and AUC and discovered that F1 is better than AUC. The integration of all feature categories achieved a better performance than the individual category of pragmatic and incongruity features. This research also evaluated the performance of the dropout layer hyperparameter and it achieved better performance than the fixed percentage like 10% of dropout parameter of the AutoML based Bayesian optimization. Proposed AutoML framework DeepConcat evaluated best pretrain models BiLSTM-DNN and CNN-CNN-DNN to transfer knowledge across domains like Amazon reviews and Dialog discussion comments (text) using the last strategy, full layer, and our fade-out freezing strategies. In the transfer learning fade-out strategy outperformed the existing state-of-the-art model BiLSTM-DNN, the performance is 0.98 F1 on tweets, 0.85 F1 on Amazon reviews, and 0.87 F1 on the dialog discussion SCV2-Gen dataset. Further, all strategies with various domains can be compared for the best model selection

Indian Contribution to Language Sciences in Non-Western Tradition: With Reference to Arabic

Language study relates itself to both ontology and epistemology. Both ontological and epistemological investigations have been the subject of debate and discussion in different civilizations producing a number of grammatical traditions other than the West. Arab, China, India and the ancient Near East can also boast of language traditions of greater antiquity. In terms of richness of insight and comprehensiveness of scope, both India and the Arab compete on equal terms with the West, where each grew independently of the others and for the most part developed separately, drawing on the resources of the culture within which it grew. Hence, there is strong need to have a study of comparative grammatical theory to which Indian, Arabs and Chinese also belong, centring on the questions of: What has been the importance of these theories explanatory categories appear in historically unrelated linguistic theory, and if they do, why? This perspective would bring new dimension to the study of linguistic theory and would not remain at the level of redressing the overwhelming emphasis on the European tradition in the study of history of linguistics

Analysis of combined approaches of CBIR systems by clustering at varying precision levels

The image retrieving system is used to retrieve images from the image database. Two types of Image retrieval techniques are commonly used: content-based and text-based techniques. One of the well-known image retrieval techniques that extract the images in an unsupervised way, known as the cluster-based image retrieval technique. In this cluster-based image retrieval, all visual features of an image are combined to find a better retrieval rate and precisions. The objectives of the study were to develop a new model by combining the three traits i.e., color, shape, and texture of an image. The color-shape and color-texture models were compared to a threshold value with various precision levels. A union was formed of a newly developed model with a color-shape, and color-texture model to find the retrieval rate in terms of precisions of the image retrieval system. The results were experimented on on the COREL standard database and it was found that the union of three models gives better results than the image retrieval from the individual models. The newly developed model and the union of the given models also gives better results than the existing system named cluster-based retrieval of images by unsupervised learning (CLUE)

Surgical Ventricular Restoration: An Operation To Reverse Remodeling - The Basic Science (Part I)

Congestive heart failure as a consequence of ischemic heart disease is an increasing medical problem. Notwithstanding the huge advances in the medical and conventional surgical management of heart failure, eventual outcomes remain suboptimal. This 2 part article outlines the magnitude of the problem, the limitations of conventional therapies as they exist, and the use of newer procedures that directly address the restoration of ventricular pump function

Surgical Ventricular Restoration: An Operation to Reverse Remodeling - Clinical Application (Part II)

The first part of the article dealt with the basic science behind the evolution of ventricular restoration procedures and the rationale for the use of novel surgical techniques. The second part describes the preoperative workup of patients in advanced heart failure, the core information required to determine the surgical approach and the essential principles and techniques of ventricular restoration. It then examines the effects of ventricular restorative procedures on pump function and clinical outcomes, the results of the worldwide experience with ventricular restoration and concludes with more recent advances in this field

METACOGNITIVE ABILITY AND PERCEPTION OF THE BARRIERS TO BECOME ENTREPRENEUR: A STUDY OF THE UNDERGRADUATE-LEVEL BUSINESS STUDENTS OF THREE UNIVERSITIES IN KHULNA REGION OF BANGLADESH

Metacognitive ability refers to one’s knowledge and the mechanism how the people control the process of generating and applying such knowledge in order to maximize learning.  This paper focuses on exploration of the influence of metacognitive abilities of the university students in their perceptions of the barriers to the formation of their intentions to become entrepreneur. Based on the extant literature, two hypotheses were developed and tested using Partial Least Squares based on Structural Equation Modeling (PLS-SEM). To test the hypotheses, primary data were collected from the 3rd year students of the business administration departments of three universities from Khulna, the third largest city in the south-western part of Bangladesh. This study found that cognitive knowledge and cognitive regulation positive affects perception of barrier to be an entrepreneur. This might prove helpful to the nascent entrepreneurs by broadening their outlook.  Article visualizations

Near field communication enabled mobile payments: preliminary study

The ubiquitous computing has made consumers life easy, it has given the new way to interact with family and friends and perform many activities which were impossible in previous time. One of the profound achievement of ubiquitous computing is Mobile Payment and an advanced mode of the mobile payment is the near field communication mobile payment. In this study the authors have proposed theoreti-cal near field communication mobile payment model that is based on extended unified technology acceptance and use of technology (UTAUT2) .In this paper, the author have performed the pilot study to validate the variables and to verify their reliability among the proposed items. The results has proven that there is a reliability among the items in variables, as the Cronbach’s alpha value for the vari-ables is above or equal to 0.7