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<title>Year-2022</title>
<link>http://repository.iiitd.edu.in/xmlui/handle/123456789/1083</link>
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<pubDate>Fri, 10 Apr 2026 20:02:36 GMT</pubDate>
<dc:date>2026-04-10T20:02:36Z</dc:date>
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<title>Predictors of countries' positions on lethal autonomous weapons systems</title>
<link>http://repository.iiitd.edu.in/xmlui/handle/123456789/1231</link>
<description>Predictors of countries' positions on lethal autonomous weapons systems
Soni, Prabhat; Priyadarshi, Praveen (Advisor)
Finding what does (and doesn't) predict countries' positions on lethal autonomous weapons systems (LAWS) could be very valuable in informing the decisions of countries and NGOs. This report tests the predictive power of the following six considerations on countries' positions on banning LAWS: domestic development of LAWS, ethics and human rights, military requirements, public opinion on LAWS, technical capabilities of a country, and trade potential of LAWS. This reports finds a signifi cant correlation between countries' positions on banning LAWS and military requirements, and technical capabilities of a country. On the other hand, it does not  find a significant correlation with domestic development of LAWS, ethics and human rights, public opinion, and trade potential. We also construct a multiple linear regression model using variables identifi ed to be significantly correlated and use it to predict the position on banning LAWS of countries which don't have a public position yet. We also discuss some implications of our results for various actors in the LAWS space.
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<pubDate>Sun, 01 May 2022 00:00:00 GMT</pubDate>
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<dc:date>2022-05-01T00:00:00Z</dc:date>
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<title>A repository of wheels for embedded systems</title>
<link>http://repository.iiitd.edu.in/xmlui/handle/123456789/1230</link>
<description>A repository of wheels for embedded systems
Kushwah, Nikhil; Bhattacharya, Arani (Advisor)
A wheel file is a pre-compiled package that can be installed with pip, which is the package manager for Python. This can make installing and using certain modules on a Raspberry Pi much easier, eliminating the need to compile the module from source code. This can save time and make the installation process more user-friendly, particularly for users who are not familiar with compiling software from source code. In this project, I aim to develop a repository containing wheel files for the latest and essential Raspberry Pi modules. This would help users to directly download and install the wheel file for the required module without spending time configuring dependencies and building it.
</description>
<pubDate>Thu, 01 Dec 2022 00:00:00 GMT</pubDate>
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<dc:date>2022-12-01T00:00:00Z</dc:date>
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<title>Building ontology models and knowledge graphs for healthcare data</title>
<link>http://repository.iiitd.edu.in/xmlui/handle/123456789/1229</link>
<description>Building ontology models and knowledge graphs for healthcare data
Garg, Yuvraj; Balooja, Mudit; Mutharaju, Vijaya Raghava (Advisor)
Medical information from various sources has to be integrated and compiled together to provide a better understanding of a patient’s health. Mappings between different standards and domain ontologies are constructed to facilitate this very issue. In this report, we discuss our bit of contribution and the process of solving this by building ontology model. Upper ontology is constructed using three Covid-19 ontologies. These ontologies are searched on the internet which are related to covid-19. All the steps involved in building and integrating this system have been explained.
</description>
<pubDate>Thu, 01 Dec 2022 00:00:00 GMT</pubDate>
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<dc:date>2022-12-01T00:00:00Z</dc:date>
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<title>Introducing ‘nocoalias’ attribute to improve context-sensitive alias analysis in LLVM</title>
<link>http://repository.iiitd.edu.in/xmlui/handle/123456789/1228</link>
<description>Introducing ‘nocoalias’ attribute to improve context-sensitive alias analysis in LLVM
Manas; Kedia, Piyus (Advisor)
The technique of alias analysis enables us to determine which memory locations can be accessed via different access paths. But finding objects satisfying aliasing sets is hard. We present a context-sensitive approach to improve alias analysis. In this compile-time approach, we check for aliasing between various function arguments at the call-site and propagate this information by means of an attribute to the function definition. This allows the optimizer to obtain better information about the function parameters, and hence open opportunities for various optimizations in the function definition itself.
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<pubDate>Thu, 01 Dec 2022 00:00:00 GMT</pubDate>
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<dc:date>2022-12-01T00:00:00Z</dc:date>
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