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Digital Terror Crimes
Get PDFTerror actors operating within armed conflict have weaponized social media by using these platforms to threaten and spread images of brutality in order to taunt, terrify, and intimidate civilians. These acts or threats of violence are terror, a prohibited war crime in which acts or threats of violence are made with the primary purpose of spreading terror among the civilian population. The weaponization of terror content through social media is a digital terror crime.This article is the first to argue that the war crime of terror applies to digital terror crimes perpetrated through social media platforms. It situates digital terror crimes within the existing jurisprudence on terror at ad hoc international and hybrid criminal tribunals. Terror is an autonomous war crime within international criminal law, but all previous convictions for terror have occurred within the context of an underlying criminal act. Digital terror crimes are different: The underlying act of social media use is not necessarily a war crime outside the crime of terror. In addition to examining the ways that digital terror crimes can be committed during armed conflict, this article considers the various actors who could be implicated in the perpetration and distribution of digital terror
Learning by Doing, Productivity, and Growth: New Evidence on the Link between Micro and Macro Data
Get PDFSingle Field of View Calibration Through Estimating Three Mutually Orthogonal Vanishing Points for Spatial Data Collection in Traffic Scenes
No full textAccurately extracting the three mutually orthogonal vanishing points plays a vital role in the field of view calibration for many surveillance-based traffic applications. However, the paucity of parallel lines along the dominant directions in many traffic scenes engenders the inapplicability of the current methods for a successful calibration. This research proposed a novel vanishing point estimating method for traffic scenes. This method capitalizes on both the road scene and moving vehicles for the determination of the dominant directions of the real-world coordinate frame. It also exploits distinctive edgelets for the direct identification of vanishing point candidates. Both lab and field experiments were undertaken to assess the performance of the proposed method. The results signified the advances of the method in traffic scenes with scarce parallel line features and eliminating the need for trial-and-error parameter tuning in different scenes
Discovering and Understanding High Performance Materials using Density Functional Theory: Quantum Mechanical Simulations and the Consequences of Symmetry
Get PDFThere are two primary ways that atomic level modeling data is used: materials prediction and understanding materials properties. This dissertation work encom- passes two studies, each of which explore one application. Both studies rely on the highly successful density functional theory (DFT) formalism but differ in that two different implementations of DFT are used on two different high performance materials. The first study on bulk magnesium (Mg) metal alloys explores materials prediction and relies on VASP, a commercially maintained plane-wave DFT code which has been used extensively to successfully study a wide range of materials. [1] The approach used in this first study is to ‘experiment’ within computational quantum mechanical simulations to improve the elastic properties of bulk Mg by altering its HCP lattice structure. We systematically study the influence of adding lithium (Li) as an alloy for two reasons: to maintain the lightweight benefits of Mg, and Li naturally occurs in a body centered cubic (BCC) crystal structure. The hypothesis is that an alloy with a more symmetric crystal structure will show im- proved properties, however we do not place any symmetry restrictions on the results of the structure search. We find that the addition of Li to Mg does improve the elastic properties of the resulting alloys; however it does not necessarily increase the symmetry. Five structures are found which belong to the convex hull, three of which are previously unreported. The second DFT study seeks to understand the electronic environment within lead sulfur (PbS) semiconductor nano-structures and utilizes the open-source Octopus code, designed for electron-ion dynamics in finite systems using time-dependent DFT in real time and real space and which has also been bench-marked extensively [2]. The aim of the second study is to understand at the most fundamental levels the impact reduced symmetry has on the electronic states and transitions at the level of the individual IR-light-absorbing quantum dot. We employ three toy models to isolate the impacts of reduced coordination, Pb-rich structures, and Peierls distortions. An in-depth analysis of the bonding through the charge density and electron localization function shows that the metavalent bonding observed in bulk PbS persists in the nanoscale regime. Changing the stoichiometry too far away from Pb:S = 1:1 results in the loss of semiconducting character and an overall metallic character prevails. When we place particular attention on the effects of atomic coordination, we observe enhanced electron localization clustered around the lowest coordinated atoms. Peierls distortions intensify the clustering behavior which lowers the energy of the occupied electronic states and increases the energy of the unoccupied states as deduced from density of states plots. The change in the electron localization is substantial only for a significant amount of low-coordinated atoms. A conclusion is made with an outlook to future work