<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-18T22:55:58Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/139472" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/139472</identifier><datestamp>2022-01-15T03:05:47Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor">Graves, Stephen</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="advisor">Slocum, Alexander</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="advisor">Kim, Louis</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author">Kendall, Thomas P.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Operations Research Center</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2022-01-14T15:13:25Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2022-01-14T15:13:25Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued">2021-06</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="submitted">2021-07-01T00:44:40.677Z</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">https://hdl.handle.net/1721.1/139472</dim:field>
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   <dim:field mdschema="dc" element="description" qualifier="abstract">An accurate soldier is a lethal soldier, lethal soldiers make an effective army, and an effective army is a deterrent to war. In this paper we aim to apply optimization methods to nonlinear trajectory models to make every soldier more lethal with their assigned weapon system (and hunters more humane with their rifles). We first discover a way to optimize the trajectory of the average soldier's bullet over a specific range in a way that can be immediately implemented with negligible impact to current infrastructure, equipment, practices, and procedures. Next, we develop the mathematics behind an aiming device which considers the angle at which a weapon is aimed and the angle at which the weapon is tilted, and automatically adjusts to produce the optimal bullet trajectory over a specified range. We design this device while minimizing power consumption, minimizing weight, and avoiding the use of additional sensors such as laser range finders. Finally, we model a similar device intended for civilian hunters and military snipers which guarantees minimized deviation at an estimated range.</dim:field>
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   <dim:field mdschema="dc" element="publisher">Massachusetts Institute of Technology</dim:field>
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   <dim:field mdschema="dc" element="title">Optimizing Weapon Precision</dim:field>
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   	&lt;Title>Optimizing Weapon Precision&lt;/Title>
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   	&lt;PublicationDate>2021-06&lt;/PublicationDate>
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        	&lt;DisplayName>Kendall, Thomas P.&lt;/DisplayName>
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            &lt;DisplayName>Massachusetts Institute of Technology&lt;/DisplayName>
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   	&lt;Abstract>An accurate soldier is a lethal soldier, lethal soldiers make an effective army, and an effective army is a deterrent to war. In this paper we aim to apply optimization methods to nonlinear trajectory models to make every soldier more lethal with their assigned weapon system (and hunters more humane with their rifles). We first discover a way to optimize the trajectory of the average soldier&amp;apos;s bullet over a specific range in a way that can be immediately implemented with negligible impact to current infrastructure, equipment, practices, and procedures. Next, we develop the mathematics behind an aiming device which considers the angle at which a weapon is aimed and the angle at which the weapon is tilted, and automatically adjusts to produce the optimal bullet trajectory over a specified range. We design this device while minimizing power consumption, minimizing weight, and avoiding the use of additional sensors such as laser range finders. Finally, we model a similar device intended for civilian hunters and military snipers which guarantees minimized deviation at an estimated range.&lt;/Abstract>
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