SemImput: Bridging Semantic Imputation with Deep Learning for Complex Human Activity Recognition

The recognition of activities of daily living (ADL) in smart environments is a well-known and an important research area, which presents the real-time state of humans in pervasive computing. The process of recognizing human activities generally involves deploying a set of obtrusive and unobtrusive sensors, pre-processing the raw data, and building classification models using machine learning (ML) algorithms. Integrating data from multiple sensors is a challenging task due to dynamic nature of data sources. This is further complicated due to semantic and syntactic differences in these data sources. These differences become even more complex if the data generated is imperfect, which ultimately has a direct impact on its usefulness in yielding an accurate classifier. In this study, we propose a semantic imputation framework to improve the quality of sensor data using ontology-based semantic similarity learning. This is achieved by identifying semantic correlations among sensor events through SPARQL queries, and by performing a time-series longitudinal imputation. Furthermore, we applied deep learning (DL) based artificial neural network (ANN) on public datasets to demonstrate the applicability and validity of the proposed approach. The results showed a higher accuracy with semantically imputed datasets using ANN. We also presented a detailed comparative analysis, comparing the results with the state-of-the-art from the literature. We found that our semantic imputed datasets improved the classification accuracy with 95.78% as a higher one thus proving the effectiveness and robustness of learned models

Prevalence of Paramphistomum cervi in different sheep breeds of Balochistan (Pakistan)

The prevalence of Paramphistomum cervi infestation in Balochi, Babrik and Harnai sheep breeds from Balochistan (Pakistan) was studied during September to December 2010. For this purpose, rumen of slaughtered sheep in Quetta City and surroundings (n=1,200) were examined. Results showed significant differences (

Exposure to NO<inf>2</inf> in occupationalbuilt environmnets in urban centre in Lahore

Increased economic growth, urbanisation and substantial rise in automobile vehicles has contributed towards the elevated levels of air pollution in major cities in Pakistan. Aone week study was conducted by using passive samplers to assess NO2 concentration in occupational built environments at two most congested and populated sites of Lahore. Both sites were locatedon the busy roads of Lahore. At Site-I the highest concentration was in outdoors followed by corridor and indoor. While at Site II all the sampling location wereindoors and level were comparable to that of outdoor levelsat Site I. The results suggest the likely contribution of ambient sources in exposure to indoor NO2 in educational and other occupational built environments in urban centres

Systems of education governance and cultures of justice in Ireland, Scotland and Pakistan

This chapter compares the issue of cultures of justice in the systems of education governance in three education systems: Ireland, Scotland and Pakistan. The focus for the comparison are the current policies which shape the regulation of education. These policies were reviewed to identify key issues relating to social justice and equality, decision-making and accountability. From the analysis of each system, three central issues were identified: firstly, the improvement of a state education system; secondly, the degree of decentralisation and centralisation in governance structures and thirdly, the expectations placed on school leaders. The chapter concludes by discussing the tensions between the drive for system improvement and opportunities for school leaders to build strategies to address issues of inequality in schools

An Assortment of Evolutionary Computation Techniques (AECT) in gaming

© 2020, Springer-Verlag London Ltd., part of Springer Nature. Real-time strategy (RTS) games differ as they persist in varying scenarios and states. These games enable an integrated correspondence of non-player characters (NPCs) to appear as an autodidact in a dynamic environment, thereby resulting in a combined attack of NPCs on human-controlled character (HCC) with maximal damage. This research aims to empower NPCs with intelligent traits. Therefore, we instigate an assortment of ant colony optimization (ACO) with genetic algorithm (GA)-based approach to first-person shooter (FPS) game, i.e., Zombies Redemption (ZR). Eminent NPCs with best-fit genes are elected to spawn NPCs over generations and game levels as yielded by GA. Moreover, NPCs empower ACO to elect an optimal path with diverse incentives and less likelihood of getting shot. The proposed technique ZR is novel as it integrates ACO and GA in FPS games where NPC will use ACO to exploit and optimize its current strategy. GA will be used to share and explore strategy among NPCs. Moreover, it involves an elaboration of the mechanism of evolution through parameter utilization and updation over the generations. ZR is played by 450 players with varying levels having the evolving traits of NPCs and environmental constraints in order to accumulate experimental results. Results revealed improvement in NPCs performance as the game proceeds

Synthesis of Boron-Doped Zinc Oxide Nanosheets by Using Phyllanthus Emblica Leaf Extract: A Sustainable Environmental Applications

The use of Phyllanthus emblica (gooseberry) leaf extract to synthesize Boron-doped zinc oxide nanosheets (B-doped ZnO-NSs) is deliberated in this article. Scanning electron microscopy (SEM) shows a network of synthesized nanosheets randomly aligned side by side in a B-doped ZnO (15 wt% B) sample. The thickness of B-doped ZnO-NSs is in the range of 20–80 nm. B-doped ZnO-NSs were tested against both gram-positive and gram-negative bacterial strains including Staphylococcus aureus, Pseudomonas aeruginosa, Klebsiella pneumonia, and Escherichia coli. Against gram-negative bacterium (K. pneumonia and E. coli), B-doped ZnO displays enhanced antibacterial activity with 26 and 24 mm of inhibition zone, respectively. The mass attenuation coefficient (MAC), linear attenuation coefficient (LAC), mean free path (MFP), half-value layer (HVL), and tenth value layer (TVL) of B-doped ZnO were investigated as aspects linked to radiation shielding. These observations were carried out by using a PTW® electron detector and VARIAN® irradiation with 6 MeV electrons. The results of these experiments can be used to learn more about the radiation shielding properties of B-doped ZnO nanostructures

Quinpramine Ameliorates Rat Experimental Autoimmune Neuritis and Redistributes MHC Class II Molecules

Activation of inflammatory cells is central to the pathogenesis of autoimmune demyelinating diseases of the peripheral nervous system. The novel chimeric compound quinpramine—generated from imipramine and quinacrine—redistributes cholesterol rich membrane domains to intracellular compartments. We studied the immunological and clinical effects of quinpramine in myelin homogenate induced Lewis rat experimental autoimmune neuritis (EAN), a model system for acute human inflammatory neuropathies, such as the Guillain-Barré syndrome. EAN animals develop paresis of all limbs due to autoimmune inflammation of peripheral nerves. Quinpramine treatment ameliorated clinical disease severity of EAN and infiltration of macrophages into peripheral nerves. It reduced expression of MHC class II molecules on antigen presenting cells and antigen specific T cell proliferation both in vitro and in vivo. Quinpramine exerted its anti-proliferatory effect on antigen presenting cells, but not on responder T cells. Our data suggest that quinpramine represents a candidate pharmaceutical for inflammatory neuropathies