Efficient Human Activity Recognition in Large Image and Video Databases

Vision-based human action recognition has attracted considerable interest in recent research for its applications to video surveillance, content-based search, healthcare, and interactive games. Most existing research deals with building informative feature descriptors, designing efficient and robust algorithms, proposing versatile and challenging datasets, and fusing multiple modalities. Often, these approaches build on certain conventions such as the use of motion cues to determine video descriptors, application of off-the-shelf classifiers, and single-factor classification of videos. In this thesis, we deal with important but overlooked issues such as efficiency, simplicity, and scalability of human activity recognition in different application scenarios: controlled video environment (e.g.~indoor surveillance), unconstrained videos (e.g.~YouTube), depth or skeletal data (e.g.~captured by Kinect), and person images (e.g.~Flicker). In particular, we are interested in answering questions like (a) is it possible to efficiently recognize human actions in controlled videos without temporal cues? (b) given that the large-scale unconstrained video data are often of high dimension low sample size (HDLSS) nature, how to efficiently recognize human actions in such data? (c) considering the rich 3D motion information available from depth or motion capture sensors, is it possible to recognize both the actions and the actors using only the motion dynamics of underlying activities? and (d) can motion information from monocular videos be used for automatically determining saliency regions for recognizing actions in still images

Consumption and Employment Effects of Income Redistribution in Pakistan

The argument that growth and equality are two opposite objectives and the conviction that if the former is preferred in the short run, the latter will automatically follow in the long run, though very popular in the past, have become somewhat controversial in recent years. Available evidence from the developing countries does not seem to support the 'trickle down' theory. It is being increasingly felt that the solution to the problem of poverty does not lie in mere maximization of the GNP. Economists have now started stressing the need for 'direct attack on poverty' (6, pp.42- 44] and for specific policies with growth implications for different groups in the Society (2, p. xiii] . Redistribution of income among different groups is therefore emerging as an important policy objective in many developing countries, including Pakistan

Integrated Hazard Identification (IHI): A Quick Accident Analysis and Quantification Method for Practitioners

There are many techniques for hazard identification and are divided into shortcut, standard and advanced techniques. Among these, HAZOP and What-If techniques are mostly engaged by practitioners in the chemical process industry. Both of these have certain advantages and limitations, i.e., HAZOP is structured, and what-if covers broad range of scenarios. There is no hazard identification method, which can cover a broad range of scenarios and is structured in nature. For this purpose, a new technique namely integrated hazard identification (IHI) is proposed in this article that integrates HAZOP and What-If. The methodology is demonstrated via hazard identification study of urea synthesis section. Risk ranking is used to sort out the worst-case scenario. This worst-case scenario is further studied in detail for quantification that is performed using the ALOHA software. This quantification has assisted to detect ammonia concentrations in nearby control room and surroundings for worst-case scenario. It is revealed that if ammonia pump is not stopped within 10 minutes, concentration inside and outside the control room may reach to 384 ppm and 2630 ppm, compared to 1100 ppm (AEGL-3). Thus the proposed method would be easy, time saving and covers more details and would be handy for practicing engineers working in different chemical process industries

History matters in making Lahore sustainable

Lahore, the second-largest city of Pakistan, is facing sharp population growth and economic development coupled with increased motorisation and a deteriorating urban environment. This is due to a long history of investment into roads and low-density suburban housing development in Lahore which increases motorisation. This paper provides a historical overview of urban planning in Lahore by shedding light on the Mughal and the British period of development followed by the post-independence planning paradigm in the city. This paper examines the contradictions and uncertainties that have characterised urban planning in Lahore in the pre and post-independence period by using a sustainable city and sustainable transport literature. The analysis shows that Lahore traditionally attracted investment in the high-quality roads infrastructure (flyovers, underpasses and a ring road) and recently in the country first ever Bus Rapid Transit (BRT) system (2013) and Metro Train project (2018) in the city. The paper argues that the Lahore BRT and Metro train projects can provide a window of opportunity to redefine transport and land use issues and offer a transit-oriented development (TOD) solutions in Lahore

How Much Output should be Produced by the Firm? An Analysis

In this study, the main objective of the firm is to determine output and price level; we have taken the time series data of the firm and have applied the ordinary least square technique. We find out the equilibrium point of the firm where marginal revenue is equal to marginal cost and at that point firm earn the maximum profit and we also determine the price level of the firm. The output level that the firm should produce would be of 3922 units, at this point its total cost is 1131611, total revenue is 1115890, marginal revenue is 308.6689, marginal cost is 308.6702 and optimal price is 284.5206. Keywords: Price and Output Determination, Empirical Study, MR = M