Natural Language Processing for Enterprise Applications

Researchers are concentrating on more efficient communication technologies that can emulate human interactions and comprehend natural languages and human emotions as a result of people's growing reliance on computer-assisted systems. Unstructured data, which is deemed useless, has increased due to the issue of information overload in every industry, including business, healthcare, education, etc. In this context, natural language processing (NLP) is one of the efficient technologies that may be used with more sophisticated technologies, such as machine learning, artificial intelligence, and deep learning, to enhance the interpretation and processing of natural language. In addition to improving human-computer interaction, this can also enable massive amounts of useless and unstructured data to be analyzed and formatted in numerous industrial applications. This will produce significant results that can improve decision-making and hence increase operational effectiveness. This chapter introduces the idea of NLP, its background, and its current state while also going through examples of its use in various industrial fields. Keywords: Natural Language Processing, Artificial Intelligence, Machine Learning

Dynamics of Crossover from a Chaotic to a Power Law State in Jerky Flow

We study the dynamics of an intriguing crossover from a chaotic to a power law state as a function of strain rate within the context of a recently introduced model which reproduces the crossover. While the chaotic regime has a small set of positive Lyapunov exponents, interestingly, the scaling regime has a power law distribution of null exponents which also exhibits a power law. The slow manifold analysis of the model shows that while a large proportion of dislocations are pinned in the chaotic regime, most of them are pushed to the threshold of unpinning in the scaling regime, thus providing insight into the mechanism of crossover.Comment: 5 pages, 3 figures. In print in Phy. Rev. E Rapid Communication

Eliminating Health Discrepancies: Insights through Free market or State control

Healthcare inequality or healthcare disparity refers to the differences in the quality of health and health care across different populations. This may include differences in the prevalence of disease, health outcomes, or access to health care across racial, ethnic, gender, and socioeconomic groups. Differences among populations in the presence of disease and health outcomes are well documented in many areas. In the United States, disparities are well documented in minority populations such as African Americans, Native Americans, Asian Americans, and Latinos, with these groups having higher incidence of chronic diseases, higher mortality, and poorer overall health outcomes. For example, the cancer incidence rate among African Americans is 10% higher than among whites, and adult African Americans and Latinos have approximately twice the risk as whites for developing diabetes. Similarly, disparities in the overall level of health in individuals also exist between differing socioeconomic groups, with lower-status socioeconomic groups generally having poorer health and higher rates of chronic illness including obesity, diabetes, and hypertension. Those in lower socioeconomic status groups receive less consistent primary care, which is positively correlated to overall level of health in the recipient. Similarly, in England, people living in deprived areas were found to receive around 70% less provision relative to need compared with the most affluent areas for both knee and hip replacements

Leadership for Higher Education – Role of a Dean

The role of the academic dean is often a difficult one to describe. As a leader in higher education the dean has various responsibilities and many challenges to face that tend to evolve with the ever-changing face of higher education. The role of the academic dean is one that is multifaceted, challenging and often ambiguous. (Walker, 2000) The dean is a person the students could go to in times of trouble and in times of prosper, and to learn from the dean about life. It is essential that deans have the required knowledge base, skills and abilities to perform effectively in this demanding role

Dental Public Health! A Mistaken Identity

The dental public health field has been expanding in scope & complexity with more emphasis being placed on the total dental care delivery system and its impact on oral health status. A broadly accepted definition of “dental public health” has been given by Downer 1994: “The science and art of preventing oral disease, promoting oral health and improving quality of life through the organized efforts of society” (Downer et al,1994). A broader definition was made ten years later as follows: “The science and art of preventing oral disease, promoting oral health and improving quality of life through the organized efforts and informed choices of society, organizations, public and private, communities and individuals” (Pine & Harris 2007). The purpose of an oral health care system is to influence the population’s way of life so that oral health is promoted or maintained and oral disease prevented; and to promote adequate treatment to those members of the population affected by oral disease so that disease is arrested at an early stage and loss of function is prevented. These functions apply whether the service is in a developing or developed country

Ethical Issues in Higher Education and Scientific Research: Erosion of Academic Integrity

Ethics is the cornerstone of dental research or for that matter any research. Authorship in a scientific research is an important issue which requires considerable debate. The pressure to publish is well-established in the university community. Faculty member’s performance and promotion are judged by the number of published articles in academic scholarly journals. If survival means publish or perish, any and every effort to see one’s name in print becomes important. In such a situation, we should not be surprised to see the operation of the cliché, “You scratch my back, I’ll scratch yours” (Lazar, 1995)

DEVELOPMENT OF ANTIOXIDANT RICH INSTANT BISCUIT MIX

Objective: Bakery products are important processed foods, commonly consumed across the world. Bakery products have become essential and significant components of the dietary profile of the people. Among that biscuits are the fast growing bakery products in India, because of consumer demand for convenient, safety, low cast, shelf life, verity taste and flavor but those are lack in nutrients and antioxidants. Methods: To increase the nutrient content in biscuit mix, Wheat flour was added with maida and sugar at three variations (V1-50:50, V2-60:40, V3-70:30) and subjected to organoleptic evaluation. Antioxidant mix (Poshak Pro mix) was formulated using antioxidant rich foods like Finger millet, Black Gram Dhal, Spinach, Carrot, Guava and Sesame seeds. These were processed and formulated into three mixes (Finger millet based mix, Black Gram Dhal based mix and Carrot based mix) and subjected to DPPH radical scavenging test. The mix having highest activity was selected and incorporated into wheat flour biscuit mix at three variations (V1-20:80, V2-3:70, V3-40:60) and subjected to organoleptic evaluation. The accepted variation was analyzed for nutrient and shelf life at polythene and aluminum foil covers. Results: Among the three wheat flour: Maida variations, V3-70:30 was selected in organoleptic evaluation. In DPPH radical scavenging test Finger Milled based mix was selected and incorporated into selected wheat flour biscuit mix at three variations. V1 (20:80) was selected and nutrients analysis showed that it is rich in β-carotene. In shelf life study, both (polythene and aluminum foil) covers were accepted for packaging. Conclusion: The study proved that local commodities rich in antioxidants can be utilized effectively and economically to improve the health status of the people

Spoof detection using time-delay shallow neural network and feature switching

Detecting spoofed utterances is a fundamental problem in voice-based biometrics. Spoofing can be performed either by logical accesses like speech synthesis, voice conversion or by physical accesses such as replaying the pre-recorded utterance. Inspired by the state-of-the-art \emph{x}-vector based speaker verification approach, this paper proposes a time-delay shallow neural network (TD-SNN) for spoof detection for both logical and physical access. The novelty of the proposed TD-SNN system vis-a-vis conventional DNN systems is that it can handle variable length utterances during testing. Performance of the proposed TD-SNN systems and the baseline Gaussian mixture models (GMMs) is analyzed on the ASV-spoof-2019 dataset. The performance of the systems is measured in terms of the minimum normalized tandem detection cost function (min-t-DCF). When studied with individual features, the TD-SNN system consistently outperforms the GMM system for physical access. For logical access, GMM surpasses TD-SNN systems for certain individual features. When combined with the decision-level feature switching (DLFS) paradigm, the best TD-SNN system outperforms the best baseline GMM system on evaluation data with a relative improvement of 48.03\% and 49.47\% for both logical and physical access, respectively