The Scientist Who Came in from the Cold: Heinz Barwich's Flight from the GDR

Maddrell, John, 'The Scientist Who Came in from the Cold: Heinz Barwich's Flight from the GDR', Intelligence and National Security (2005) 20(4) pp.608-630 RAE2008

Biologically Inspired Approaches to Automated Feature Extraction and Target Recognition

Ongoing research at Boston University has produced computational models of biological vision and learning that embody a growing corpus of scientific data and predictions. Vision models perform long-range grouping and figure/ground segmentation, and memory models create attentionally controlled recognition codes that intrinsically cornbine botton-up activation and top-down learned expectations. These two streams of research form the foundation of novel dynamically integrated systems for image understanding. Simulations using multispectral images illustrate road completion across occlusions in a cluttered scene and information fusion from incorrect labels that are simultaneously inconsistent and correct. The CNS Vision and Technology Labs (cns.bu.edulvisionlab and cns.bu.edu/techlab) are further integrating science and technology through analysis, testing, and development of cognitive and neural models for large-scale applications, complemented by software specification and code distribution.

CEDI: A Neural Model of Colour Vision, with Applications to Image Processing and Classification

Air Force Office of Scientific Research (F49620-01-1-0423); National Geospatial-Intelligence Agency (NMA 201-01-1-2016); National Science Foundation (SBE-035437, DEG-0221680); Office of Naval Research (N00014-01-1-0624)

Laminar Cortical Dynamics of Visual Form and Motion Interactions During Coherent Object Motion Perception

How do visual form and motion processes cooperate to compute object motion when each process separately is insufficient? A 3D FORMOTION model specifies how 3D boundary representations, which separate figures from backgrounds within cortical area V2, capture motion signals at the appropriate depths in MT; how motion signals in MT disambiguate boundaries in V2 via MT-to-Vl-to-V2 feedback; how sparse feature tracking signals are amplified; and how a spatially anisotropic motion grouping process propagates across perceptual space via MT-MST feedback to integrate feature-tracking and ambiguous motion signals to determine a global object motion percept. Simulated data include: the degree of motion coherence of rotating shapes observed through apertures, the coherent vs. element motion percepts separated in depth during the chopsticks illusion, and the rigid vs. non-rigid appearance of rotating ellipses.

Self-Organizing Information Fusion and Hierarchical Knowledge Discovery: A New Framework Using Artmap Neural Networks

Classifying novel terrain or objects from sparse, complex data may require the resolution of conflicting information from sensors woring at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when eveidence variously suggests that and object's class is car, truck, or airplane. The methods described her address a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an object's class is car, vehicle, and man-made. Underlying relationships among classes are assumed to be unknown to the autonomated system or the human user. The ARTMAP information fusion system uses distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierachical knowlege structures. The fusion system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships. The procedure is illustrated with two image examples, but is not limited to image domain.

Neural Network and Bioinformatic Methods for Predicting HIV-1 Protease Inhibitor Resistance

This article presents a new method for predicting viral resistance to seven protease inhibitors from the HIV-1 genotype, and for identifying the positions in the protease gene at which the specific nature of the mutation affects resistance. The neural network Analog ARTMAP predicts protease inhibitor resistance from viral genotypes. A feature selection method detects genetic positions that contribute to resistance both alone and through interactions with other positions. This method has identified positions 35, 37, 62, and 77, where traditional feature selection methods have not detected a contribution to resistance. At several positions in the protease gene, mutations confer differing degress of resistance, depending on the specific amino acid to which the sequence has mutated. To find these positions, an Amino Acid Space is introduced to represent genes in a vector space that captures the functional similarity between amino acid pairs. Feature selection identifies several new positions, including 36, 37, and 43, with amino acid-specific contributions to resistance. Analog ARTMAP networks applied to inputs that represent specific amino acids at these positions perform better than networks that use only mutation locations.

A Neural Model of Visually Guided Steering, Obstacle Avoidance, and Route Selection

A neural model is developed to explain how humans can approach a goal object on foot while steering around obstacles to avoid collisions in a cluttered environment. The model uses optic flow from a 3D virtual reality environment to determine the position of objects based on motion discotinuities, and computes heading direction, or the direction of self-motion, from global optic flow. The cortical representation of heading interacts with the representations of a goal and obstacles such that the goal acts as an attractor of heading, while obstacles act as repellers. In addition the model maintains fixation on the goal object by generating smooth pursuit eye movements. Eye rotations can distort the optic flow field, complicating heading perception, and the model uses extraretinal signals to correct for this distortion and accurately represent heading. The model explains how motion processing mechanisms in cortical areas MT, MST, and VIP can be used to guide steering. The model quantitatively simulates human psychophysical data about visually-guided steering, obstacle avoidance, and route selection.

CONFIGR: A Vision-Based Model for Long-Range Figure Completion

CONFIGR (CONtour FIgure GRound) is a computational model based on principles of biological vision that completes sparse and noisy image figures. Within an integrated vision/recognition system, CONFIGR posits an initial recognition stage which identifies figure pixels from spatially local input information. The resulting, and typically incomplete, figure is fed back to the “early vision” stage for long-range completion via filling-in. The reconstructed image is then re-presented to the recognition system for global functions such as object recognition. In the CONFIGR algorithm, the smallest independent image unit is the visible pixel, whose size defines a computational spatial scale. Once pixel size is fixed, the entire algorithm is fully determined, with no additional parameter choices. Multi-scale simulations illustrate the vision/recognition system. Open-source CONFIGR code is available online, but all examples can be derived analytically, and the design principles applied at each step are transparent. The model balances filling-in as figure against complementary filling-in as ground, which blocks spurious figure completions. Lobe computations occur on a subpixel spatial scale. Originally designed to fill-in missing contours in an incomplete image such as a dashed line, the same CONFIGR system connects and segments sparse dots, and unifies occluded objects from pieces locally identified as figure in the initial recognition stage. The model self-scales its completion distances, filling-in across gaps of any length, where unimpeded, while limiting connections among dense image-figure pixel groups that already have intrinsic form. Long-range image completion promises to play an important role in adaptive processors that reconstruct images from highly compressed video and still camera images.

A Neural Model of Visually Guided Steering, Obstacle Avoidance, and Route Selection

A neural model is developed to explain how humans can approach a goal object on foot while steering around obstacles to avoid collisions in a cluttered environment. The model uses optic flow from a 3D virtual reality environment to determine the position of objects based on motion discontinuities, and computes heading direction, or the direction of self-motion, from global optic flow. The cortical representation of heading interacts with the representations of a goal and obstacles such that the goal acts as an attractor of heading, while obstacles act as repellers. In addition the model maintains fixation on the goal object by generating smooth pursuit eye movements. Eye rotations can distort the optic flow field, complicating heading perception, and the model uses extraretinal signals to correct for this distortion and accurately represent heading. The model explains how motion processing mechanisms in cortical areas MT, MST, and posterior parietal cortex can be used to guide steering. The model quantitatively simulates human psychophysical data about visually-guided steering, obstacle avoidance, and route selection.

Laminar Cortical Dynamics of Visual Form and Motion Interactions During Coherent Object Motion Perception

How do visual form and motion processes cooperate to compute object motion when each process separately is insufficient? Consider, for example, a deer moving behind a bush. Here the partially occluded fragments of motion signals available to an observer must be coherently grouped into the motion of a single object. A 3D FORMOTION model comprises five important functional interactions involving the brain’s form and motion systems that address such situations. Because the model’s stages are analogous to areas of the primate visual system, we refer to the stages by corresponding anatomical names. In one of these functional interactions, 3D boundary representations, in which figures are separated from their backgrounds, are formed in cortical area V2. These depth-selective V2 boundaries select motion signals at the appropriate depths in MT via V2-to-MT signals. In another, motion signals in MT disambiguate locally incomplete or ambiguous boundary signals in V2 via MT-to-V1-to-V2 feedback. The third functional property concerns resolution of the aperture problem along straight moving contours by propagating the influence of unambiguous motion signals generated at contour terminators or corners. Here, sparse “feature tracking signals” from, e.g., line ends, are amplified to overwhelm numerically superior ambiguous motion signals along line segment interiors. In the fourth, a spatially anisotropic motion grouping process takes place across perceptual space via MT-MST feedback to integrate veridical feature-tracking and ambiguous motion signals to determine a global object motion percept. The fifth property uses the MT-MST feedback loop to convey an attentional priming signal from higher brain areas back to V1 and V2. The model's use of mechanisms such as divisive normalization, endstopping, cross-orientation inhibition, and longrange cooperation is described. Simulated data include: the degree of motion coherence of rotating shapes observed through apertures, the coherent vs. element motion percepts separated in depth during the chopsticks illusion, and the rigid vs. non-rigid appearance of rotating ellipses.

Diagnóstico de las relaciones bilaterales entre Colombia y República Dominicana en torno al tema del narcotráfico desde 1998 hasta el 2010

El tema del narcotráfico ha sido ampliamente tratado, así como el caso de las drogas en Colombia, pero la afectación de dicho problema no ha sido analizada desde la República Dominicana y mucho menos desde la relación bilateral entre esta y Colombia. Aunque el tema es de gran relevancia en la agenda internacional, así como en la agenda interna de cada uno de estos Estados, no es el tema principal en la relación bilateral, donde los asuntos comerciales tienen mayor importancia, aún cuando hay ciertos mecanismos que buscan eliminar el tráfico ilegal de estupefacientes. En esta investigación, se busca dar un diagnóstico de las relaciones bilaterales y de aquellos instrumentos existentes, específicamente aquellos implementados desde la acogida internacional del término responsabilidad compartida en el año 1998 hasta el año 2010, para determinar la efectividad de los mismos y de aquellos factores que no son precisamente resultantes de las relaciones bilaterales pero que sí afectan de una u otra manera el tráfico de drogas ilegales entre estos dos países. Así, se buscará encontrar las debilidades, en los instrumentos bilaterales entre Colombia y República Dominicana y hacer recomendaciones para hacerlos más efectivos.

Efectos de la reducción del nivel del Lago Chad sobre la Seguridad Regional (Nigeria, Níger, Chad y Camerún) durante el período de 2000-2010

El Lago Chad ha sido durante varias décadas, una fuente de supervivencia económica para millones de personas que habitan en cuatro Estados a saber; Nigeria, Níger, Chad y Camerún. No obstante, el cambio climático, el aumento acelerado de la población, la explotación insostenible y la mala regulación de los Estados ribereños han sido los principales factores que han dado lugar, en la última década, a la dramática reducción del nivel del Lago Chad. Teniendo en cuenta que los Estados aledaños al Lago, se encuentran inmersos en una Interdependencia Compleja, este nuevo contexto, ha tenido un impacto directo en la región, debido a que ha agravado otras variables económicas, sociales, ambientales y políticas, dejando un ambiente de inseguridad regional. De esta manera, la reducción de la Cuenca del Lago Chad representa una amenaza compartida que vincula estrechamente a Nigeria, Níger, Chad y Camerún, lo que permite vislumbrar la existencia de un Subcomplejo de Seguridad Regional.

Análisis de las tensiones geopolíticas entre Kirguistán y Uzbekistán por el Valle de Fergana y sus recursos energéticos durante el periodo 2001-2010

Las tensiones geopolíticas entre Kirguistán y Uzbekistán por el Valle de Fergana durante el periodo 2001-2010 a partir de un análisis histórico de la formación de la población y la influencia de los diferentes imperios en la región. Adicionalmente, los aspectos relativos a la importancia de los recursos energéticos en el Valle de Fergana como la configuración de las tensiones generadas entre estos dos países, haciendo énfasis en el conflicto étnico latente que se ha generado en la zona. De se utilizarán la teoría constructivista de Alexander Wendt y la teoría de la geopolítica de Yves Lacoste.

Análisis de inversión extranjera directa por parte del grupo de los BRIC hacia los sectores estratégicos de Colombia

El siguiente documento da a conocer el comportamiento de la Inversión Extranjera Directa (IED) de los países denominados BRIC (Brasil, Rusia, India y China) en Colombia. De acuerdo a lo anterior, en el presente trabajo, se realizó un análisis general de la IED entrante en el país suramericano que buscaba establecer los principales inversores; además de determinar los sectores más atractivos. Posteriormente, se observó la magnitud de la inversión que realizan los países BRIC en Colombia y en el mundo, con el fin de efectuar una comparación que permitiera determinar que tan significativa es la inversión que se realiza en el Estado Colombiano frente a la que es efectuada por estas naciones a nivel global. Igualmente, se consideró las industrias a las que la IED está dirigida, el grado de beneficio que representa para la población y si existe la posibilidad de enfocarla hacia otros sectores estratégicos o si se recomienda encauzarla hacia aquellos que hoy en día son el principal foco de inversión.

Análisis de la relación comercial entre la República de Colombia y la República de Costa Rica

Dadas las relaciones de cooperación internacional que presentan las Repúblicas de Colombia y Costa Rica, que se evidencia en los fuertes vínculos comerciales existentes entre las dos naciones, Proexport por medio de su oficina comercial en Costa Rica, ha mantenido al tanto la situación en la que se desenvuelve la alianza comercial entre Colombia y Costa Rica. Él último de estos informes, demuestra la potencialidad de Costa Rica como un mercado para los bienes colombianos y una posibilidad para los exportadores nacionales que buscan mercados para sus productos o servicios. Este proyecto de investigación surge, con el objetivo de analizar las relaciones bilaterales y contribuir al desarrollo de la economía emergente que presenta el país. Para ello, en primera instancia se realiza un proceso de contextualización desde aspectos demográficos hasta históricos. En seguida y a manera descriptiva, se expone los diversos bienes y servicios que se intercambian entre las dos naciones con el fin de identificar oportunidades que se podrían ofrecer y afectar una vez se firme el tratado. Finalmente, se evalúa y analiza cada uno de los sectores emergentes de Colombia con el objeto de motivar la inversión en el país para generar de tal manera, un incremento en la producción, logrando abrir las puertas de la economía colombiana a un socio estratégico como lo es Costa Rica y contribuir poco a poco al desarrollo del comercio sustentable entre las dos naciones.