Search results

This paper aims to develop a real-time pothole detection system to improve mapping, localization and path planning, reducing vehicle instability and accident risks. Efficient mapping, accurate localization and optimal path planning stand as prerequisites to realizing accident-free navigation. Despite their significance, existing literature often overlooks the real-time detection of potholes, which poses a considerable risk, particularly during nighttime operations. Potholes contribute to vehicle imbalance, trajectory tracking errors, abrupt braking, wheel skidding, jerking and steering overshoot, all of which can lead to accidents.

Unmanned vehicles constitute a critical domain within robotics research, necessitating reliable autonomous navigation for their optimal functioning. This research paper addresses the gap in current methodologies by leveraging a Convolutional Neural Network (CNN)-based approach to detect potholes, facilitating the generation of an efficient environmental map. Furthermore, a hybrid solution is proposed, integrating an improved Ant Colony Optimization (ACO) algorithm with modified Bezier techniques, complementing the CNN approach for accident-free and time-efficient unmanned vehicle navigation. The conventional Bezier technique is enhanced by incorporating new control points near sharp turns, mitigating rapid trajectory convergence and ensuring collision-free paths.

The hybrid solution, combining CNN with path smoothing techniques, is rigorously tested in various real-time scenarios. Experimental results demonstrate that the proposed technique achieves a 100% reduction in collisions in favorable conditions, a 4.5% decrease in path length, a 100% reduction in sharp turns and a significant 23.31% reduction in total time lag compared to state-of-the-art techniques such as conventional ACO, ACO+ Bezier and ACO+ midpoint Bezier, Improved ACO, hybrid ACO+ A*.

The proposed technique provides a proficient solution in the field of unmanned vehicles for accident-free time efficient navigation in an unstructured environment.

This paper aims at understanding the causes of low adoption of hybrid rice technology. The paper also assesses the impact of adoption of hybrids and modern varieties on crop yield, vis-à-vis the old or traditional varieties.

Using unit-level data from a large-scale survey of farm households (19,877 paddy cultivators), the authors applied multi-nomial regression method to understand the factors for adoption of hybrid rice and instrumental variable method of regression to estimate its impact.

The findings demonstrate that in India, hybrid rice is often grown on relatively poor soils, resulting in greater irrigation costs and for other inputs, such as fertilizers. Further, farmers' poor access to information on the traits of hybrid rice and the associated agronomic practices, as well as poor access to financial resources, hampers efforts to scale up its adoption. More importantly, the findings reveal that the relative yield advantage of hybrids over open-pollinated modern varieties is not large enough to incentivize the rapid adoption of hybrid rice technology.

Given the higher cost of hybrids than the inbred varieties, enhancing paddy cultivators' access to financial resources can accelerate the adoption of hybrid rice in India.

The study is based on unit level data from a large-scale, nationally representative survey of farm households, comprising a sample of 19,877 paddy cultivators, spread across states in India.

The main aim of this paper is to assess the relevance of caste-based social networks in the dissemination of technologies and innovations in the Indian agriculture.

Using the unit-level data from a large-scale farm survey, this paper constructs a multidimensional index of social networks encompassing households' castes and information sources within the administrative boundaries of a district and subsequently assesses its association with the adoption of modern seeds of staple food crops.

There is a strong effect of caste-based networks on the adoption of modern seeds of different crops, but the effect is linked to the stage of technological change, i.e. the network effect is stronger for the crop that has experienced late technological change. Further, the behavior of network members is found to have a bigger impact on the individuals' technology adoption decisions as compared to the characteristics of individuals in the network.

Given likely, increases in demand for diverse information and limited outreach of public extension systems, the findings suggest that in a socially heterogeneous society the caste-based social networks can serve as an important channel for the dissemination of information and innovations.

What is unique in this paper is that it constructs a multidimensional index of social networks embedding the farm households' castes and information sources within the administratively defined boundaries of a geographical region.

This paper aims to examine the traditional business communities and family businesses of India, their emergence and sustained growth.

The authors analyze the role of business communities in family businesses of India and identify business communities that have still sustained and marked a global presence.

Business communities such as Marwaris have the knack for business activities and are leaders of family businesses in India today, who have sustained their past success and continue to create new histories. Other traditional business communities such as Parsis, Sindhis, Chettiars and Gujarati banias have not been able to sustain much. Possible reasons were switching to white-collar jobs, taking up diplomacy and other professions, inter caste marriages, international migration in search of business and Indian government policies.

This study provides a useful source of information for academics, policy-makers and economists.

Traditional business communities populate the list of family businesses that have marked their global presence. This paper identifies various factors that are responsible for the growth and sustainability of these business communities.

The study clarifies the role of business communities in domestic economic development.

The paper explored traditional business communities of India and assessed their role in family businesses of India that currently mark a global presence.

The learning outcomes are as follows: to understand the cultural and ethical dimensions revolving around the issue of female feticide; to apply the lens of institutional theory with respective change management measures; and to analyze and evaluate the impact of such intervention programs such as Beti Bachao Beti Padhao in the context of emerging economies such as India.

This case attempts to highlight the innovative and effective governance approach by the Government of Rajasthan (India) and, in particular, the State Health Assurance Agency to curb the menace of female feticide and the rising cases of abortion and sex determination in an attempt to favor a male child. The case concentrates on mainly three dimensions of Indian societal ecosystem, namely, the grave concern of preference of male child over female child leading to widespread cases of female feticide in different states in India with specific focus on the state of Rajasthan; the role of cultural dimension which primarily drives such preferential treatment in rural and urban areas in India; and the importance of using effective policy measures in monitoring various activities, introduction of incentive schemes to patients for preventing sex determination and promoting the birth of female child.

This case can be used as a teaching material in the Public Policy course – Social Welfare and Health Policy, Policy interventions, organization theory and change management at the Graduate/MBA level.

Teaching notes are available for educators only.

CSS 10: Public Sector Management.