Two-stream deep learning architecture-based human action recognition

Human action recognition (HAR) based on Artificial intelligence reasoning is the most important research area in computer vision. Big breakthroughs in this field have been observed in the last few years; additionally, the interest in research in this field is evolving, such as understanding of actions and scenes, studying human joints, and human posture recognition. Many HAR techniques are introduced in the literature. Nonetheless, the challenge of redundant and irrelevant features reduces recognition accuracy. They also faced a few other challenges, such as differing perspectives, environmental conditions, and temporal variations, among others. In this work, a deep learning and improved whale optimization algorithm based framework is proposed for HAR. The proposed framework consists of a few core stages i.e., frames initial preprocessing, fine-tuned pre-trained deep learning models through transfer learning (TL), features fusion using modified serial based approach, and improved whale optimization based best features selection for final classification. Two pre-trained deep learning models such as InceptionV3 and Resnet101 are fine-tuned and TL is employed to train on action recognition datasets. The fusion process increases the length of feature vectors; therefore, improved whale optimization algorithm is proposed and selects the best features. The best selected features are finally classified using machine learning (ML) classifiers. Four publicly accessible datasets such as Ut-interaction, Hollywood, Free Viewpoint Action Recognition using Motion History Volumes (IXMAS), and centre of computer vision (UCF) Sports, are employed and achieved the testing accuracy of 100%, 99.9%, 99.1%, and 100% respectively. Comparison with state of the art techniques (SOTA), the proposed method showed the improved accuracy

Spectrum of Vaccine Preventable Diseases Amongst Children in Isolation Ward of Tertiary Care Hospitals

OBJECTIVE: The objective of the study is to determine the spectrum of vaccine preventable diseases amongst children in pediatric medical unit of  tertiary care hospitals and also determine its relationship with the vaccination status. METHODOLOGY: It was a cross sectional study held at isolation ward of pediatric therapeutic division of  The Children’s Hospital and University of Child Health Sciences and Shaikh Zayed Hospital Lahore from December 2019 to November, 2020. We included children aged between 2 months to 16 years. After getting parental consent, precise history taken and examination done. Patients admitted with different vaccine preventable diseases analyzed. RESULTS: One hundred and twenty patients were enrolled. Amongst them, 55.83% were male and 44.17 % were female. Amongst spectrum of diseases, most common was chicken pox 43(35.83%) followed by measles 32(26.6 %), tetanus 20 (16.6%), diphtheria 13(10.83 %), mumps 12 (10%). CONCLUSION: Amongst diseases, chicken pox was the commonest one. Non-vaccination is the major reason that children are presenting with these potentially morbid diseases. Moreover, vaccine against varicella should be included in EPI Programme for our country. &nbsp

A Low-Overhead Countermeasure against Differential Power Analysis for AES Block Cipher

This paper presents the employment of a DPA attack on the NIST (National Institute of Standards and Technology) standardized AES (advance encryption standard) protocol for key retrieval and prevention. Towards key retrieval, we applied the DPA attack on AES to obtain a 128-bit secret key by measuring the power traces of the computations involved in the algorithm. In resistance to the DPA attack, we proposed a countermeasure, or a new modified masking scheme, comprising (i) Boolean and (ii) multiplicative masking, for linear and non-linear operations of AES, respectively. Furthermore, we improved the complexity involved in Boolean masking by introducing Rebecca’s approximation. Moreover, we provide a novel solution to tackle the zero mask problem in multiplicative masking. To evaluate the power traces, we propose our custom correlation technique, which results in a decrease in the calculation time. The synthesis results for original implementation (without countermeasure) and inclusion of countermeasure are given on a Zynq 7020 FPGA (Artix-7 device). It takes 424 FPGA slices when implemented without considering the countermeasure, whereas 714 slices are required to implement AES with the inclusion of the proposed countermeasure. Consequently, the implementation results provide the acceptability of this work for area-constrained applications that require prevention against DPA attacks

Dengue virus serotype 2 (DEN-2): the causative agent of 2011-Dengue epidemic in Pakistan

Abstract Introduction: Dengue virus (DENV) is an arthropod-borne virus that belonged to the Flaviviridae viral family. Four known serotypes DEN-1 through DEN-4 do exist and circulate in diverse geographical regions of the world causing epidemics. The management of dengue patients, and especially dengue hemorrhagic fever (DHF)/Dengue shock syndrome (DSS) cases, has been a challenge in Pakistan now days. Method: We have carried out a comprehensive study of the current outbreaks of dengue virus infection on molecular level with the aim to find out the common serotype/s of DENV responsible for this outbreak using PCR, real-time PCR and nucleotide sequencing targeting the C-prM gene junction. For this purpose total 1129 serum samples received between from start of August till end of November 2011 from all the major hospitals of Lahore, Punjab at Division of Molecular Virology, National Centre of Excellence in Molecular Biology (CEMB) University of the Punjab Lahore were utilized for the DENV diagnosis and serotypes/genotypes analysis. Results: Male female ratio of the suspected dengue patients was 2.4:1. Their mean age were 31.14 + 16.03 (SD) years ranging from 9 months to 90 years. Out of these 1129 serum samples, total 930 (82.37%) were found infected with DENV. Out of the 930 DENV RNA positive samples, 893 (96.02%) had DEN-2 Am. J. Biomed. Sci. 2012, 4(4), 307-315; doi: 10.5099/aj120400307 © 2012 by NWPII. All rights reserved. 308 and 37 (3.97%) sample had concurrent infection with serotypes 2 and 3. Conclusion: Based on the results of this study we conclude that DEN-2 is the responsible genotype for the current dengue epidemic that started from the beginning of year 2011 and is continuing till now. The additional serotype detected in the current study was serotype 3 that remained in very low frequency in Pakistan for last several decades