Micro-expression Recognition using Spatiotemporal Texture Map and Motion Magnification

Micro-expressions are short-lived, rapid facial expressions that are exhibited by individuals when they are in high stakes situations. Studying these micro-expressions is important as these cannot be modified by an individual and hence offer us a peek into what the individual is actually feeling and thinking as opposed to what he/she is trying to portray. The spotting and recognition of micro-expressions has applications in the fields of criminal investigation, psychotherapy, education etc. However due to micro-expressions’ short-lived and rapid nature; spotting, recognizing and classifying them is a major challenge. In this paper, we design a hybrid approach for spotting and recognizing micro-expressions by utilizing motion magnification using Eulerian Video Magnification and Spatiotemporal Texture Map (STTM). The validation of this approach was done on the spontaneous micro-expression dataset, CASMEII in comparison with the baseline. This approach achieved an accuracy of 80% viz. an increase by 5% as compared to the existing baseline by utilizing 10-fold cross validation using Support Vector Machines (SVM) with a linear kernel

Semantic similarity between words and sentences using lexical database and word embeddings

Calculating the semantic similarity between sentences is a long-standing problem in the area of natural language processing. The semantic analysis field has a crucial role to play in the research related to the text analytics. The meaning of the word in general English language differs as the context changes. Hence, the semantic similarity varies significantly as the domain of operation differs. For this reason, it is crucial to consider the appropriate definition of the words when they are compared semantically. We present an unsupervised method that can be applied across multiple domains by incorporating corpora based statistics into a standardized semantic similarity algorithm. To calculate the semantic similarity between words and sentences, the proposed method follows an edge-based approach using a lexical database. When tested on both benchmark standards and mean human similarity dataset, the methodology achieves a high correlation value for both word (Pearsons Correlation Coefficient = 0.8753) and sentence similarity (PCC = 0.8793) while comparing Rubenstein and Goodenough standard; and the SICK dataset (PCC = 0.8324) outperforming other unsupervised models. We use the semantic similarity algorithm and extend it to compare the Learning Objectives from course outlines. The course description provided by instructors is an essential piece of information as it defines what is expected from the instructor and what he/she is going to deliver during a particular course. One of the key components of a course description is the Learning Objectives section. The contents of this section are used by program managers who are tasked to compare and match two different courses during the development of Transfer Agreements between various institutions. This research introduces the development of semantic similarity algorithms to calculate the similarity between two learning objectives of the same domain. We present a methodology which deals with the semantic similarity by using a previously established algorithm and integrating it with the domain corpus to utilize domain statistics. The disambiguated domain serves as a supervised learning data for the algorithm. We also introduce Bloom Index to calculate the similarity between action verbs in the Learning Objectives referring to the Bloom's taxonomy. We also study and present the approach to calculate the semantic similarity between words under the word2vec model for a specific domain. We present a methodology to compile a corpus for a specific domain using Wikipedia. We then present a case to show the variance in the semantic similarity between words using different corpora. The core contributions of this thesis are a semantic similarity algorithm for words and sentences, and the corpus compilation of a specific domain to train the word2vec model. We also provide the practical uses of algorithms and the implementation

Concept of Artavavaha Srotas

In Ayurveda, the concept of Srotas has been propagated very specifically. They are integral part of the body. Body is composed of numerous Srotas which have a significant role in maintenance of equilibrium of body elements. They are responsible for maintenance of health as well as disease condition. Srotas is a channel through which different elements undergo transformation, circulation and transportation. Pathological changes occurs in the body due to Srotodushti, Srotosanga etc

Audio diarization for LENA data and its application to computing language behavior statistics for individuals with autism

The objective of this dissertation is to develop diarization algorithms for LENA data and study its application to compute language behavior statistics for individuals with autism. LENA device is one of the most commonly used devices to collect audio data in autism and language development studies. LENA child and adult detector algorithms were evaluated for two different datasets: i) older children dataset consisting of children already diagnosed with autism spectrum disor- der and ii) infants dataset consisting of infants at risk for autism. I-vector based diarization algorithms were developed for the two datasets to tackle two scenarios: a) some amount of labeled data is present for every speaker present in the audio recording and b) no labeled data is present for the audio recording to be diarized. Further, i-vector based diarization methods were applied to compute objective measures of assessment. These objective measures of assessment were analyzed to show they can reveal some aspects of autism severity. Also, a method to extract a 5 minute high child vocalization audio window from a 16 hour day long recording was developed, which was then used to compute canonical babble statistics using human annotation.Ph.D

Effect of Chandana Bala Lakshadi Taila Abhyanga with Poshaka Laddu & Nutri Recharge Powder in Bala Shosha (Kuposhana Janya Vyadhi)

Introduction: In Ayurveda Bala Shosha is known as Kuposhan Janya Vyadhi and it is viewed under Malnutritional or PEM disorder. Malnutrition is a common health problem in preschool children of developing countries including in India. As per WHO poor feeding of infant and young children resulting in under nutrition is the single and most important factor for diseases. The malnourished child needs proper Ahara and Aaushadh for normal growth and protecting disease. So, we have made suitable plan to a child.   Aim: To evaluate the effect of Candana Bala Lakshadi Taila Abhyanga, Poshaka Laddu, Nurticharge Powder internally in Bala Shosha (Kuposhana Janya Vyadhi). Material & Method: The clinical study was conducted in 30 Malnourished Children pre and post evaluation without control. The Study setting Department of Koumarbhritya (Bal-Roga), Shubhdeep Ayurved Medical College, Indore M.P. This study is come under the project of Govt. of M.P. in supervision of Indore collector and funded by Govt. of M.P. Result: The effect of Nuticharge powder, Poshak Laddu & Abhyanga on child weight and M.U.A.C is statistically significant (P= 0.01). It showed that the treatment significantly increases the weight and mid under arm circumference of malnourished children. Conclusion: Here in this study a small group was taken for the study which is equated with the PEM & Kuposhana Janya Vyadhi

Biological Role of Chalcones in Medicinal Chemistry

Chalcones are promising synthons and bioactive scaffolds of great medicinal interest due to their numerous pharmacological and biological activities. They are well recognized to possess antimicrobial, anticancer, antitubercular, antioxidant, anti-inflammatory, antileishmanial, and other significant biological activities. This chapter highlights recent updates and applications of chalcones as biologically, pharmacologically, and medicinally important entities

Yb(OTf)3 Catalyzed Synthesis, Antimicrobial and Insecticidal activity of some Biscoumarins

Published ArticleIn the present study, we report Yb(OTf)3 catalyzed synthesis of biscoumarins by pseudo three-component reaction of aldehyde and 4-hydroxycoumarin. The synthesized biscoumarins were evaluated for antimicrobial and insecticidal activity. Results of antimicrobial activity were found to be moderate to good in terms of zones of inhibition and MIC values against E. coli, P. vulgaris and S. aureus. The compounds were inactive against the used fungal strains except B4 in case of Penicillium. Insecticidal activity of the biscoumarins B-1, B-3, B-5 and B-11 was found to be good exhibiting 70-75% mortality effect on Callosobruchus maculatus

COVID-19: Recent updates on SARS-CoV-2 and Preventing its Community Transmission in India by 21 Days Lockdown

The current pandemic of COVID-19 has caused havoc all over world since its emergence and rapid spread. Within three months the virus SARS-CoV-2 which was isolated from pneumonia cases in Wuhan City, Hubei Province, China in late December 2019, has affected almost all countries. India reported its first case of COVID-19 from state of Kerala on January 30, 2020, a student returned from city of Wuhan. Till date in India the disease had affected 12759 patients with 420 deaths. With every passing day the mysterious virus is been uncovered with its unique characteristics enabling the researcher to unfold the various methods including hand washing and social distancing to curtail the pandemic. Measures like 21 days lockdown to certain extent are effective but considering asymptomatic spreaders, extended measured lockdowns will be useful in the long term war against COVID-19. Till the vaccine and therapeutic solutions are derived, answer to pandemic and SARS-CoV-2 lies in lockdown, social distancing, contact tracing and containment

Detection and molecular characterization of ascarid nematode infection (Toxascaris leonina and Toxocara cati) in captive Asiatic lions (Panthera leo persica).

The objective of this study was to investigate the ascarid infection in Asiatic lions using scat samples, based on microscopic analysis, PCR amplification of the ITS-2 region of ribosomal DNA and sequence analysis of the amplicons. Microscopic analysis indicated the presence of eggs of Toxascaris leonina in eleven of the sixteen scat samples analysed and in one of these eleven scats eggs of Toxocara cati were also detected. In five of the scats eggs were not detectable. The presence of T. leonina in all the infected samples was also confirmed by PCR amplification of the ITS-2 of ribosomal RNA gene and five of these also showed amplicons corresponding to T. cati, respectively. Toxocara canis infection was not observed in any of the scat samples. Nucleotide sequence analysis of the ITS-2 region indicated 97% to 99% similarity with T. leonina and T. cati, respectively. To our knowledge, this is the first molecular characterization of ascarid infection in captive Asiatic lions from a zoological garden of India. This study also indicates that Asiatic lions are more prone to infection either with T. leonina or T. cati and the parasite is not host specific

Anonymous Schedule Generation Using Genetic Algorithm

In this proposed system, a genetic algorithm is applied to automatic schedule generation system to generate course timetable that best suit student and teachers needs. Preparing schedule in colleges and institutes is very difficult task for satisfying different constraints. Conventional process of scheduling is very basic process of generating schedule for any educational organization .This study develop a practical system for generation of schedule .By taking complicated constraints in consideration to avoid conflicts in schedule. Conflicts means that generate problem after allocation of time slots