An automatic recognition of human activities enables their use in several interesting applications of daily life. This dissertation emphases on the analysis of human activities in a visual surveillance scenario and the classification of physical activities in the therapeutic procedure using visual data. The first part of the dissertation proposes a robust gait representation to recognise the identity of a person using his/her walking style, dealing with its several real world challenges as well as taking into consideration the effects of cross-view recognition. In the second part, a complete framework is proposed to capture and analyse the movement of different body parts in human which is useful in the clinical assessment to detect any movement disorders and the assessment of the desired therapeutic program.
In this autobiographical, historical and analytical perspective on Pakistan, Najm takes a closer look at the judicial revolution in Pakistan. Pakistani Judiciary becomes the reader's navigator through meandering paths of Pakistan's internal battles for institutional growth. This is also a diplomat's view of the socio-historical evolution of Pakistan. His outlook combines an insider's insights and limitations with an extensive historical and cultural learning process that includes living, working and pursuing academic interests abroad. He also unravels fundamental contradictions that militate against emergence of equitable educational opportunities in Pakistan. He meets thus a general reader, a policy maker, legal community abroad and at home, democracy advocates, the Diaspora, the students and analysts on their turf. Born in Multan, Pakistan, Najm is currently a candidate for MA in Law and Diplomacy, at The Fletcher School of Law and Diplomacy, Tufts University.
The average age of people has increased due to advances in health sciences, which has led to an increase in the elderly population. This is positive news, but it also raises questions about the quality of independent living for older people. Clinicians use Activities of Daily Living (ADLs) to assess older people's ability to live independently. In recent years, portable computing devices have become more present in our daily lives. Therefore, a software system that can detect ADLs based on sensor data collected from wearable devices is beneficial for detecting health problems and supporting health care. In this context, this book presents several machine learning-based approaches for human activity recognition (HAR) using time-series data collected by wearable sensors in the home environment. In the first part of the book, machine learning-based approaches for atomic activity recognition are presented, which are relatively simple and short-term activities. In the second part, the algorithms for detecting long-term and complex ADLs are presented. In this part, a two-stage recognition framework is also presented, as well as an online recognition system for continuous monitoring of HAR. In the third and final part, a novel approach is proposed that not only solves the problem of data scarcity but also improves the performance of HAR by implementing multitask learning-based methods. The proposed approach simultaneously trains the models of short- and long-term activities, regardless of their temporal scale. The results show that the proposed approach improves classification performance compared to single-task learning.
This is the first study to distinguish a possible link between trade liberalisation and regional disparities under dissimilar political regimes, such as autocracy and democracy. It uses Pakistan as a case study to draw broader lessons for other developing countries.
Genetically uniform cultivars in many self-pollinated cereal crops dominate commercial production in high-input environments especially due to their high grain yields and wide geographical adaptation. These cultivars generally perform well under favorable and high-input farming systems but their optimal performance cannot be achieved on marginal/organic lands or without the use of external chemical inputs (fertilizers, herbicides and pesticides). Cereal breeding programs aim at evaluating candidate lines/cultivars for agronomic, disease and quality traits in a weed free environment that makes it impossible to identify traits conferring competitive ability against weeds. Moreover, quantification of competitive ability is a complex phenomenon which is affected by range of growth traits. Above (e.g. light) and below (e.g. water and nutrients) ground resources also influence competitiveness to a greater extent. Competitiveness is quantitatively inherited trait which is heavily influenced by many factors including genotype, management, environment and their interaction. Sound plant breeding techniques and good experimental designs are prerequisites for maximizing genetic gains to breed cultivars for organically managed lands. The brief is focused on breeding wheat for enhanced competitive ability along with other agronomic, genetic and molecular studies that have been undertaken to improve weed suppression, disease resistance and quality in organically managed lands. The examples from other cereals have also been highlighted to compare wheat with other cereal crops.
Changing Patterns of Warfare between India and Pakistan analyzes how advanced nuclear technologies and the advent of disruptive technologies have affected the evolving conflict between India and Pakistan. Advanced nuclear technologies such as nuclear submarines, aircraft carriers, ballistic missile defence systems (BMDs), multiple independently targetable re-entry vehicles (MIRVs), anti-satellite weapons (ASAT); and disruptive technologies such as hypersonic weapons, artificial intelligence (AI), lethal autonomous weapons (LAWs), unmanned aerial vehicles (UAVs) / drones and space-based and cyber technologies have all complicated crisis dynamics and the domain of warfare in the region. Further, the employment of India’s compellence strategy is an indication of a change in its stance that demonstrates smart/surgical strikes are now more likely. The phenomenon of surgical strikes raises the question of how disruptive technologies will be used to gain direct/indirect military control and hence challenge the existing status quo and deterrence stability. Against this backdrop, the authors predict how this conflict may develop in the future and evaluate the ways to stabilize deterrence and regulate the militarization of artificial intelligence and disruptive technologies between India and Pakistan. This book will be of interest to all those researching and working in the fields of security studies, strategic studies, nuclear policy, deterrence thinking and proliferation/non-proliferation aspects of the nuclear weapons programme within South Asia and beyond. It will also be relevant for the academic community, policy-makers, diplomats, members of international non-governmental organizations (INGOs), professional research institutes and organizations working on India–Pakistan relations.
This innovative book analyses the growth of Deobandi Islam, a religious sect whose followers include extremist groups, through the frame of a counterculture in conflict with mainstream Muslim society. Due to its relationship with the Taliban, close links to al-Qaeda, and worldwide reach through the ‘Tablighi Jamaat’ (Proselytization Group), the Deoband Madrassah Movement has come to acquire global significance. In Pakistan, Deobandi schools have increasingly been associated with the rise of an intolerant and militant strain of Islam linked with terrorist activities.
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