242 research outputs found
How to reduce poverty in Bihar
No full textChinmaya Kumar argues that Bihar’s economic growth can spur further poverty reduction if the state government removes binding constraints for agricultural growth
Cash versus in-kind transfers: what do beneficiaries really want?
No full textMaitreesh Ghatak, Chinmaya Kumar, and Sandip Mitra examine the factors that determine whether beneficiaries prefer receiving in-kind or cash transfers
An efficient service dispersal mechanism for fog and cloud computing using deep reinforcement learning
No full textThis dataset release supports the results presented in the paper
Chinmaya Kumar Dehury, Satish Narayana Srirama, An efficient service dispersal mechanism for fog and cloud computing using deep reinforcement learning. The 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID2020)
URL: https://ieeexplore.ieee.org/document/913966
sj-docx-1-pie-10.1177_09544089221087819 - Supplemental material for Finite element analysis and experimental investigation of moving heat source model for GMAW deposited mild steel weld bead
No full textSupplemental material, sj-docx-1-pie-10.1177_09544089221087819 for Finite element analysis and experimental investigation of moving heat source model for GMAW deposited mild steel weld bead by Mohd Aslam and Chinmaya Kumar Sahoo in Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering</p
CCoDaMiC: a framework for coherent coordination of data migration and computation platforms
No full textThe amount of data generated by millions of connected IoT sensors and devices is growing exponentially. The need to extract relevant information from this data in modern and future generation computing system, necessitates efficient data handling and processing platforms that can migrate such big data from one location to other locations seamlessly and securely, and can provide a way to preprocess and analyze that data before migrating to the final destination. Various data pipeline architectures have been proposed allowing the data administrator/user to handle the data migration operation efficiently. However, the modern data pipeline architectures do not offer built-in functionalities for ensuring data veracity, which includes data accuracy, trustworthiness and security. Furthermore, allowing the intermediate data to be processed, especially in the serverless computing environment, is becoming a cumbersome task. In order to fill this research gap, this paper introduces an efficient and novel data pipeline architecture, named as CCoDaMiC (Coherent Coordination of Data Migration and Computation), which brings both the data migration operation and its computation together into one place. This also ensures that the data delivered to the next destination/pipeline block is accurate and secure. The proposed framework is implemented in private OpenStack environment and Apache Nifi
sj-pdf-1-pie-10.1177_09544089211073296 - Supplemental material for Exploring Casting Defects of AA7075 Alloy in the Gravity Die Casting Simulation of an IC Engine Block
No full textSupplemental material, sj-pdf-1-pie-10.1177_09544089211073296 for Exploring Casting Defects of AA7075 Alloy in the Gravity Die Casting Simulation of an IC Engine Block by T. Aneesh, K. Pawan, L. Mohan, P. Hari Krishna, Tapano Kumar Hotta, Chinmaya Prasad Mohanty and Manoj Gupta in Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering</p
A Combined System Metrics Approach to Cloud Service Reliability Using Artificial Intelligence
No full textIdentifying and anticipating potential failures in the cloud is an effective method for increasing cloud reliability and proactive failure management. Many studies have been conducted to predict potential failure, but none have combined SMART (self-monitoring, analysis, and reporting technology) hard drive metrics with other system metrics, such as central processing unit (CPU) utilisation. Therefore, we propose a combined system metrics approach for failure prediction based on artificial intelligence to improve reliability. We tested over 100 cloud servers’ data and four artificial intelligence algorithms: random forest, gradient boosting, long short-term memory, and gated recurrent unit, and also performed correlation analysis. Our correlation analysis sheds light on the relationships that exist between system metrics and failure, and the experimental results demonstrate the advantages of combining system metrics, outperforming the state-of-the-art
VLSI design of intelligent, Self-monitored and managed, Strip-free, Non-invasive device for Diabetes mellitus patients to improve Glycemic control using IoT
No full textTo overcome the problems of existing invasive blood glucose monitoring, like pain while pricking, uncomfortable test strips, possibilities of infections, a real-time display and 24 hours non-invasive intelligent blood glucose level monitoring system is proposed. The proposed architecture acquires data with high speed and accuracy regarding levels of blood and tissue glucose concentration in the peripheral or central blood resulting in improved glycemic control. Furthermore, the substantial random noise is filtered before the results are displayed in the real-time display monitor. The device will provide accurate readings and generate alert signals using IoT so that untoward events can be prevented due to extreme fluctuations in the blood glucose levels. The system consists of a pulsed laser diode, a photoelectric transducer, low noise amplifier, high-speed analog to digital converter (ADC), and field programmable gate array (FPGA) and the LCD. The signal to noise ratio and sampling speed are maximized. The proposed system is realized using FPGA and produces maximum efficiency and high throughput with low energy consumption.The authors gratefully acknowledge the support provided by Government Primary Health Centre, Mulanur (Dharapuram, Tirupur, Tamil Nadu)-India, Chinmaya Mission Hospital (CMH), Bengaluru-India, the Research Consultancy Institute (RCI) of Effat University-Saudi Arabia, and the KACST Technology Innovation Centre for Solid State Lighting , KAUST-Saudi Arabia
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Essays in Development Economics
No full textThis thesis consists of three chapters. In Chapter 1, we study whether access to complaintresolution systems can resolve hold-up problems in the implementation of public good
projects. We run a field experiment involving 1629 low-caste local representatives who were
unable to start public goods projects in their constituencies due to bureaucratic hurdles. We
randomize offers to file complaints regarding public good project initiation on their behalf
and track its effects. Our treat- ment leads to a 40 percentage points jump in complaint
filing rate and is effective in improving project implementation: treated constituencies see a
26% rise in public good projects. We also find that the treatment increases project initiation
in neighboring constituencies by 23%. Our analysis suggests that the mere threat of a formal
com- plaint technology could cause project initiation in neighboring wards. However, when
multiple complaints are filed against the same higher bureaucrat, resolution rates go down.
Surprisingly, treated representatives do not gain any electoral returns in the local elections
that were held two years after the treatment.
In Chapter 2, we study the distributional consequences of reservation policies in thecontext of mandated political representation (“reservation") in favour of the marginalized
Scheduled Caste (SC) groups in India. We bring to bear a wealth of data: secondary
data on public goods from across 45,000 villages, private assets from over 19 million rural
households, political candidacy data of over 300,000 candidates and a primary survey of over
8,700 households from the state of Bihar. Using a regression discontinuity design framework,
we show that reservation for SCs for the post of local government head (a) lowers SC-non-
SC disparities in access to public goods in the short-run (5 years later) and long-run (13
years later) (b) lowers inter-group private asset inequality modestly in the short-run and
substantially in the long-run (c) creates different sets of winners and losers within SCs
and non-SCs (d) has no efficiency consequences in the short-run and (e) increases political
participation and presence of SCs in local government in the long-run. We exploit a unique feature of our RD design to show that the causal impact of reservation is largest when
SCs are neither too large nor too small in number. Turning to mechanisms, we show that
(i) government schemes are better targeted towards SCs in reserved constituencies and (ii)
intra-SC heterogeneity lowers impacts of reservation.
Chapter 3 studies why minorities are underrepresented in enterprise ownership and leadershippositions in big firms. This chapter empirically investigates the role of one potential
reason for this: discrimination against minority employers by subordinate workers. I embed
a field experiment in the recruitment of entry-level workers by a set of firms based in India.
The field experiment aims to answer two main research questions: 1) Do minority employers
face discrimination from below in labor markets? 2) What are the underlying motivations?
I specifically test for two potential motives: attention discrimination and social image concerns.
Preliminary results show that applicants are 3 p.p. (26%) less likely to apply for jobs
advertised by minority employers. I also find strong evidence for ‘attention discrimination’
against minority employers
Analysis of application-based traffic load balancing over satellite links of divergent performance
No full textThe main goal of the thesis is to investigate how to optimize Quality of Experience (QoE) of users using applications over satellite links by application aware load balancing capabilities of SD-WAN. SES (Commercial satellite operator) customers want to use applications over satellite links that have high latency and are often more congested than terrestrial networks which results in lower Quality of Experience (QoE) of users. The applications have been designed and optimized for terrestrial networks, not for satellite networks. Thus, SES wants to use its hybrid (MEO/GEO) satellite network and application aware routing capabilities of SD-WAN to prioritize and steer traffic at the application layer based on intent and business rules and enforced via policy for appropriate QoE.In the thesis, work is carried out in two parts: Firstly, experiments in lab to perform performance measurement of selected widely used applications over the different satellite links (GEO, MEO and LEO). Then performance of video applications over MEO link in different congestion scenarios (Unidirectional and Bidirectional Congestion) was measured. In order to improve the performance of video applications load balancing mechanism was defined to optimize QoE of the user. Secondly, a simulation model emulating a future SD-WAN scenario on Simulink, which is used to measure QoE of multiple users is designed. A load balancing mechanism which not only optimizes the QoE for multiple users but is also a cost effective alternative to manage the QoE is proposed. It was concluded that applications belonging to the same category have varied performances in different congestion scenarios on satellite links. Hence, each application has its performance, variation and should be dealt with accordingly. Identifying performance thresholds in different scenarios is essential to derive load balancing mechanisms to improve QoE and optimize the cost. Key applications that drive the behaviour of experience should be identified (which differs in each use case and for different customers) and steered accordingly to the best possible link so that overall QoE could be improved. Recommendations on the designing of policies for different use cases and overall development of SD-WAN as a product have also been presented in the thesis.Electrical Engineering | Telecommunications and Sensing System
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