Doctor of Philosophy / Security Studies Interdepartmental Program / Andrew G. Long / David R. Stone / This dissertation research examines the effect of organizational lethality on the longevity of terrorist groups. The current scholarship has sought to understand the demise of terrorist groups through means such as group success, government repression, negotiations, internal conflict, reorientation of goals, defeat, leadership decapitation and loss of public support. However, little research is available on the determinants of terrorists’ target selection and its implications for the group’s longevity. This study evaluates the targeting patterns and preferences of 480 terrorist groups that were operational between 1980 and 2011 and disaggre- gates the victims of all terrorist attacks into combatant versus non-combatant target-types. It is hypothesized that organizational lethality – defined as the average number of civilian killings generated by each group in its home-base country – is associated with negative group reputation, which results in faster group mortality. Popular support for violence, however, can influence and result from terrorism at the same time and has been found to be inherently endogenous by many previous studies. Therefore, a Seemingly Unrelated Bivariate Probit Model is employed to examine this endogenous relationship, and the results confirm that there is a significant correlation between negative group reputation and group mortality. Moreover, the study differentiates between terrorist group activity – defined as average at- tacks generated by a group – and group lethality, and employs the Cox Proportional Hazard Model to estimate group duration. The study includes covariates like group size, ideology, positive consistency reputation and other factors affecting group longevity and mortality. The results imply that organizational lethality is associated with higher political risks for terrorist groups and tends to backfire by decreasing their survival probability. However, on the other hand, the study finds that an escalation in terrorist activity (launching more attacks) significantly increase the group longevity over time. The results of this study are tested by conducting group-specific case studies on the Afghan and Pakistani Taliban in Pak- istan using information collected from the English language Pakistani newspaper archives, and Harmony Database from Combat Terrorism Center at West Point, NY.

The phenomenon of Terrorism has perplexed and fascinated policy makers and scholars. While there has been significant amount of research on Terrorism, the dynamics or Pathologies of Terrorist Target Selection have received less attention, with few comprehensive treatises on the subject. In this paper, I review and critique existing literature on the subject, while offering a different perspective and model for this dynamic. First, I introduce a contemporary definition of terrorism and establish a framework for the analysis of Terrorist Target Selection. In Chapter 2, I posit that accurate Target Selection Forecasting Techniques need to account for the Adaptive Learning Mechanisms that Terrorist Groups adopt and existing case studies on the subject. Chapter 3 undertakes a critical literature review of Target Selection Case Studies. In Chapter 4, I suggest new research proposals that adopt this theme. In conclusion, I offer what we believe is a novel approach to understanding Terrorist Target Selection and argue that such a model should be flexible enough to work across the various Ideological Silos that Terrorist movements are bracketed into in the current Geo-Political Environment. / text

The Remote Distractor Effect (RDE) is a robust phenomenon where a saccade to a lateralised target is delayed by the appearance of a distractor in the contralateral hemifield (Walker, Kentridge, & Findlay, 1995). The main aim of this thesis was to test whether the RDE generalises to response modalities other then the eyes. In Chapter 2, the RDE was tested on saccadic and simple manual keypress responses, and on a choice discrimination task requiring a covert shift of attention. The RDE was observed for saccades, but not simple manual responses, suggesting that spatially oriented responses may be necessary for the phenomenon. However, it was unclear whether distractor interference occurred in the covert task. Chapter 4 compared the effects of distractors between spatially equivalent tasks requiring saccadic and manual aiming responses respectively. Again, the RDE was observed for the eyes but not for the hands. This dissociation was also replicated in a more naturalistic task in which participants were free to move their eyes during manual aiming. In order to examine the time-course of distractor effects for the eyes and the hands, a third experiment investigated distractor effects across a wider range of target-distractor delays, finding no RDE for manual aiming responses at distractor delays of 0, 100, or 150 ms. The failure of the RDE to generalise to manual aiming suggests that target selection mechanisms are not shared between hand and eye movements. Chapter 5 further investigated the role of distractors during covert discrimination. The first experiment showed that distractor appearance did not interfere with discrimination performance. A second experiment, in which participants were also asked to saccade toward the target, confirmed the lack of RDE for covert discrimination while saccades were slower in distractor trials. The dissociation between covert and overt orienting suggests important differences between shifts of covert attention and preparation of eye movements. Finally, Chapter 6 investigated the mechanism driving the RDE. In particular it was assessed whether saccadic inhibition (Reingold & Stampe, 2002) is responsible for the increase in saccadic latency induced by remote distractors. Examination of the distributions of saccadic latencies at different distractor delays showed that each distractor produced a discrete dip in saccadic frequency, time-locked to distractor onset, conforming closely to the character of saccadic inhibition. It is concluded that saccadic inhibition underlies the remote distractor effect.

The purpose of this thesis is to investigate the role that political ideologies plays in determining the target of insurgency movements. In order to understand how these groups operate, I use Janowitz's military establishment to apply it on the three main revolutionary ideologies of the 20th century, Khomeinism, Marxism/Leninism and Fanonian. Based on these analyses, I hypothesize the three main targets by ideology based on the clarity of the indoctrination and on the level of bureaucracy entailed in the revolutionary texts. I then proceed to compare these theories to three case studies, the Hezbollah, the FARC and finally the PKK. I try to offer an explanation on why religious insurgencies target most of their attacks towards rival factions or why nationalist left-wing groups are mostly focused on attacking security forces. I argue that a well-structured hierarchy, a reliance on the civil society and a clear definition of the political and military targets are quintessential to prevent civilian causalities. But contrarily to most papers on the topic, I find that a strict military discipline has the reversed result that expected. For instance, the FARC and the PKK have such a strict internal code of discipline that it led the members to desert the organizations by thousands and have civilians as...

There are a number of clinical options available for speech-language pathologists to choose from to analyze a child's phonological system, select treatment targets, and design intervention. Frequently, each of these areas of clinical options is viewed independently of one another or approached within an eclectic framework. In this article, an integrated and systemic approach is presented which assumes that a dynamic interaction exists among assessment, target selection, and intervention. Systemic Phonological Assessment of Child Speech, the distance metric approach to target selection, and the multiple oppositions treatment approach are described, with examples provided for each component. Finally, a case study is presented that examines the systemic approach of multiple oppositions relative to the approach of minimal pairs.

L'accélération de l'expansion de l'Univers est l'un des sujets majeurs de la cosmologie actuelle. Elle pourrait être due à une nouvelle composante, appelée énergie noire, qui représenterait 70% du bilan énergétique de l'Univers. Pour étudier sa nature à travers son équation d'état, on mesure une règle étalon fournie par les oscillations baryoniques acoustiques (BAO) à différentes valeurs de décalage vers le rouge. Cette technique a été utilisée avec succès pour la première fois en 2005 par le projet Sloan Digital Sky Survey (SDSS-II). Depuis, l'observation des BAO a été confirmée en 2012 par le projet BOSS (SDSS-III) puis eBOSS (SDSS-IV), à la fois avec des galaxies et des absorbeurs de la raie à 21 cm révélés dans des spectres de quasar. Notre groupe prépare la prochaine génération d'expériences BAO en participant à la construction du spectrographe du nouveau programme Dark Energy Spectroscopic Instrument (DESI). Ce projet va réaliser un sondage 3D de plusieurs dizaines de millions de galaxies et quasars avec le télescope Mayall de 4m en Arizona (USA). J'ai participé à la mise au point du spectrographe de DESI en collaboration avec notre partenaire industriel (WINLIGHT). J'étais aussi en charge de développer un banc optique dans le but de valider l'alignement des capteurs CCD montés dans les enceintes des cryostats. Des matrices de microlentilles sont utilisées pour projeter très précisément des grilles de spots sur les CCD. En fonction de la distortion observée des grilles, nous sommes capables de déterminer la position des CCD. En parallèle, j'ai développé des algorithmes pour la sélection des quasars cibles, les objets les plus distants qui seront observés par DESI, basée sur leurs propriétés photométriques en exploitant des techniques d'apprentissage supervisé. / The accelerating expansion of the universe is one of the main topics of modern cosmology. It may stem from a new component, so-called dark energy, which would make up 70% of the energy content of the universe. To study its nature through its equation of state, one can measure a standard ruler given by baryonic acoustic oscillations (BAO) at various redshifts or for different slices of the universe. This approach was used successfully for the first time in 2005 by the Sloan Digital Sky Survey (SDSS-II) project. Then, the BAO signal was confirmed in 2012 by the BOSS project (SDSS-III) and then by the eBOSS project (SDSS-IV), both with galaxies and HI absorbers revealed in quasar spectra. Our group is preparing the next generation of BAO experiments by taking part in building the spectrograph of the new Dark Energy Spectroscopic Instrument (DESI) program. This project will perform a 3D survey of several tens of millions of galaxies and quasars with the 4-meter Mayall telescope in Arizona (USA). I participated in the adjustments of the spectrograph of DESI in collaboration with our industrial partner (WINLIGHT). I was also in charge of developing an optical bench in order to check the alignment of the CCD sensors mounted within the crysotat vessels. Arrays of microlens are used to project very precisely grids of spots on the CCDs. We are able to infer the position of the CCDs according to the observed distortion of the grids of spots. In parallel, I developped algorithms for the selection of quasar candidates, the more distant objects that will be observed by DESI, based on their photometry properties by making use of machine learning tools.

Indiana University-Purdue University Indianapolis (IUPUI) / We use gestures frequently in daily life—to interact with people, pets, or objects. But interacting with computers using mid-air gestures continues to challenge the design of touchless systems. Traditional approaches to touchless interaction focus on exploring gesture inputs and evaluating user interfaces. I shift the focus from gesture elicitation and interface evaluation to touchless interaction mechanics. I argue for a novel approach to generate design guidelines for touchless systems: to use fundamental interaction principles, instead of a reactive adaptation to the sensing technology. In five sets of experiments, I explore visual and pseudo-haptic feedback, motor intuitiveness, handedness, and perceptual Gestalt effects. Particularly, I study the interaction mechanics in touchless target selection. To that end, I introduce two novel interaction techniques: touchless circular menus that allow command selection using directional strokes and interface topographies that use pseudo-haptic feedback to guide steering–targeting tasks. Results illuminate different facets of touchless interaction mechanics. For example, motor-intuitive touchless interactions explain how our sensorimotor abilities inform touchless interface affordances: we often make a holistic oblique gesture instead of several orthogonal hand gestures while reaching toward a distant display. Following the Gestalt theory of visual perception, we found similarity between user interface (UI) components decreased user accuracy while good continuity made users faster. Other findings include hemispheric asymmetry affecting transfer of training between dominant and nondominant hands and pseudo-haptic feedback improving touchless accuracy. The results of this dissertation contribute design guidelines for future touchless systems. Practical applications of this work include the use of touchless interaction techniques in various domains, such as entertainment, consumer appliances, surgery, patient-centric health settings, smart cities, interactive visualization, and collaboration.

Recent research has demonstrated that target selection is an important link between phonological assessment and intervention. It is a significant variable in treatment efficacy because, as suggested by Camarata and Nelson (1992), acquisition efficiency is at least predicated on the selection of targets that are addressed in intervention. Typically, speech-language pathologists have relied on phonetic factors that were based on developmental norms and/or stimulability. Specifically, those who adhered to a traditional approach to target selection chose sounds that were stimulable and early developing. This traditional approach to target selection was based on the assumption that earlier, stimulable sounds were easier to produce and followed a developmental sequence of acquisition.

There are a number of clinical options available for speech-language pathologists to choose from to analyze a child's phonological system, select treatment targets, and design intervention. Frequently, each of these areas of clinical options is viewed independently of one another or approached within an eclectic framework. In this article, an integrated and systemic approach is presented which assumes that a dynamic interaction exists among assessment, target selection, and intervention. Systemic Phonological Assessment of Child Speech, the distance metric approach to target selection, and the multiple oppositions treatment approach are described, with examples provided for each component. Finally, a case study is presented that examines the systemic approach of multiple oppositions relative to the approach of minimal pairs.

La sélection de cibles en mouvement est une tâche courante et complexe dans l'interaction homme-machine (IHM) en général et en particulier dans le domaine de la réalité virtuelle (RV). La prédiction de l'action est une solution intégrale pour aborder les problèmes liés à l'interaction. Cependant, les techniques actuelles de prédiction sont basées sur le suivi continu des actions de l'utilisateur sans prendre en compte la possibilité que les actions d'atteinte d'une cible puissent avoir une composante importante préprogrammée—cette théorie est appelé la théorie du contrôle préprogrammé.En se basant sur la théorie du contrôle préprogrammé, cette thèse explore la possibilité de prédire les actions, avant leur exécution, de sélection d'objets en mouvement. Plus spécifiquement, trois niveaux de prédiction d'action sont étudiés : 1) la performance des actions, mesurée par le temps de mouvement (TM) nécessaire pour atteindre une cible, 2) la difficulté prospective (DP), qui représente la difficulté subjective de la tâche estimée avant son exécution, 3) l'intention de l'utilisateur, qui indique la cible visée par l'utilisateur.Dans le cadre de cette thèse, des modèles de prédiction d'intention sont développés à l'aide des arbres de décision ainsi que des fonctions de classement—ces modèles sont évalués dans deux expériences en RV. Des modèles 1-D et 2-D de DP pour des cibles en mouvement basés sur la loi de Fitts sont développés et évalués dans une expérience en ligne. Enfin, des modèles de TM avec les mêmes caractéristiques structurelles des modèles de DP sont évaluées dans une expérience 3-D en RV. / Selection of moving targets is a common, yet complex task in human–computer interaction (HCI), and more specifically in virtual reality (VR). Action prediction has proven to be the most comprehensive enhancement to address moving-target selection challenges. Current predictive techniques, however, heavily rely on continuous tracking of user actions, without considering the possibility that target-reaching actions may have a dominant pre-programmed component—this theory is known as the pre-programmed control theory.Thus, based on the pre-programmed control theory, this research explores the possibility of predicting moving-target selection prior to action execution. Specifically, three levels of action prediction are investigated: 1) action performance measured as the movement time (MT) required to reach a target, 2) prospective difficulty (PD), i.e., subjective assessments made prior to action execution; and 3) intention, i.e., the target that the user plans to reach.In this dissertation, intention prediction models are developed using decision trees and scoring functions—these models are evaluated in two VR studies. PD models for 1-D, and 2-D moving- target selection tasks are developed based on Fitts' Law, and evaluated in an online experiment. Finally, MT models with the same structural form of the aforementioned PD models are evaluated in a 3-D moving-target selection experiment deployed in VR.