International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California / The Broadcast Scheduling Problem (BSP) is a well known NP-complete problem that arises in the study of wireless networks. In the BSP, a finite set of stations are to be scheduled in a time division multiple access (TDMA) frame. The objective is a collision free transmission schedule with the minimum number of TDMA slots and maximal slot utilization. Such a schedule will minimize the total system delay. We present variations of a Greedy Randomized Adaptive Search Procedure (GRASP) for the BSP. Path-relinking, a post-optimization strategy is applied. Also, a reactivity method is used to balance GRASP parameters. Numerical results of our research are reported and compared with other heuristics from the literature.

Thesis advisor: Steven D. Bruner / Peptidic natural products are produced by diverse organisms ranging from bacteria to humans. These secondary metabolites can be assembled by the ribosome or by nonribosomal peptide synthetase (NRPS) enzymatic assembly lines. The architectural complexity and biological activity of such compounds make them interesting targets for study. Frequently, nonribosomal peptides contain nonproteinogenic amino acid building blocks, and the biosynthetic routes to both ribosomal and nonribosomal peptides often utilize tailoring enzymes. These specialized enzymes catalyze mechanistically challenging reactions and provide peptidic natural products with structural motifs not normally found in proteins. Structural studies of these tailoring enzymes will further our understanding of biosynthetic pathways, and engineered tailoring enzymes could find use as promiscuous catalysts for the chemoenzymatic synthesis of natural product analogs. The L-tyrosine 2,3-aminomutase <italic>Sg</italic>TAM catalyzes the formation of &beta;-tyrosine from L-tyrosine, and is used in the biosynthetic pathway to the enediyne antitumor antibiotic C-1027. This enzyme contains the rare electrophilic prosthetic group 4-methylideneimidazole-5-one (MIO) and is homologous to the histidine ammonia lyase family of enzymes. While lyases form &alpha;,&beta;-unsaturated carboxylates as products, <italic>Sg</italic>TAM catalyzes additional chemical steps that result in an overall 2,3-amino shift. The precise mechanistic role of MIO in the ammonia lyase and aminomutase families of enzymes was actively debated for over 50 years. Here, we report the first x-ray crystal structure of an MIO-dependent aminomutase and detail the synthesis and characterization of mechanistic probes for this enzyme. Furthermore, we report several structures of <italic>Sg</italic>TAM bound to substrate analogs. These co-crystal structures reveal how <italic>Sg</italic>TAM achieves substrate recognition and suggest a specific role for MIO in catalysis. The results of our studies allow for the rational engineering of MIO-based aminomutases and ammonia lyases with altered physical properties and substrate specificities. Additionally, we are currently studying several enzymes involved in the biosynthesis of the tricyclic depsipeptide microviridin J. This ribosomal peptide natural product contains two lactones and one lactam, which are introduced by two enzymes belonging to the ATP-grasp ligase superfamily of proteins. Here, we detail the overexpression of these enzymes, MdnJ-B and MdnJ-C, in <italic>E. coli</italic> and report the optimization of conditions which lead to the crystallization of both enzymes. The structural characterization of MdnJ-B and MdnJ-C will lead to a greater understanding of macrocycle formation in ribosomal peptide biosynthesis, and engineered variants of these enzymes may find use as macrocylcization catalysts. / Thesis (PhD) — Boston College, 2009. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Chemistry.

This report presents a system for generating a stable, feasible, and reachable grasp of a polyhedral object. A set of contact points on the object is found that can result in a stable grasp; a feasible grasp is found in which the robot contacts the object at those contact points; and a path is constructed from the initial configuration of the robot to the stable, feasible final grasp configuration. The algorithm described in the report is designed for the Salisbury hand mounted on a Puma 560 arm, but a similar approach could be used to develop grasping systems for other robots.

In this thesis we use greedy randomize adaptive search procedure (GRASP) to solve the traveling salesman problem (TSP). Starting with nearest neighbor method to construct the initial TSP tour, we apply the 2-opt and the path-relinking method for the initial tour improvement. To increase 2-opt search speed, fixed-radius near neighbor search and don0t &#8722; look bit techniques are introduced. For the same reason a new efficient data structure, the reverse array, is proposed to represent the TSP tour. Computational results show that GRASP gives fairly good solutions in a short time.

Usability is one of the most important quality attributes in the new generation of software applications and computational devices. On the other hand, Model- View-Controller is a well known software architectural pattern and is widely used in its original form or its variations. The relationship between usability and the usage of Model-View-Controller, however, is still unknown. This thesis tries to contribute to this research question by providing the outcomes of a case study where a prototype has been developed in two different versions: one using Model-View-Controller and another using a widely known Object-Oriented guideline, the GRASP patterns. Those prototypes have been developed based on a non-functional prototype with a good level of usability. With the prototypes in hands, they were compared based on their design and based on the usability heuristics proposed by Nielsen. From this study, we discovered that the usage of MVC brings more advantages and disadvantages to the usability of the system than the ones that were found on the literature review. In general, the relationship between MVC and usability is beneficial, easing the implementation of usability features like validation of input data, evolutionary consistency, multiple views, inform the result of actions and skip steps in a process.

Grasping is a useful ability that allows manipulators to restrain objects to a desired location or trajectory. Whole arm grasps are grasps that use the entire surface of the manipulator to apply contacts to an object. The problem of determining the shape of an object and planning a grasp for that object with a snake-like robot are considered in this work. Existing algorithms that attempt to allow robots to plan and perform whole arm grasps are lacking, they either use restrictive assumptions or have unrealistic demands in terms of required hardware. The work presented here allows even the most basic of robots to plan grasps on unknown objects whilst using a minimum of assumptions.The new developed Octograsp algorithm is a method of gaining information regarding the shape of the object to be grasped through tactile information alone. This contact information is processed using an inverse convex hull algorithm to build a model of the object's shape and position. The performance of the algorithms are examined using both simulations and experimental hardware, it is shown that accuracy errors as low as 3.1% can be obtained. The accuracy of the model depends upon factors such as the complexity of the object and the suitability of the robot. Manipulators consisting of a large number of small links with relaxed rotational constraints outperform other configurations. It is also shown that the accuracy can be improved by between 11% and 17% by contacting the object from multiple orientations, whilst also encircling from multiple positions can provide a very large improvement of between 56% to 86%. These methods allow even the coarse contact information provided by the experimental equipment to attain a model with an accuracy error of only 26%.A second novel algorithm is described that uses the information provided from the first algorithm to plan strong grasps over the desired object. The algorithm takes, on average, 25.1 seconds to plan the grasp. The mean strength of the planned grasps is 0.3816 using the wrench ball measure, this is firmly in the very good region. Several robotic configurations, as well as objects, are used to test the performance of the algorithm. The optimal parameters of the algorithm are investigated by using the results of 51030 different tests. It is again shown that robots that consist of a large number of small links and with high rotational ability perform the best.

Robots should offer a human-like level of dexterity when handling objects if humans are to be replaced in dangerous and uncertain working environments. This level of dexterity for human-like manipulation must come from both the hardware, and the control. Exact replication of human-like degrees of freedom in mobility for anthropomorphic robotic hands are seen in bulky, costly, fully actuated solutions, while machine learning to apply some level of human-like dexterity in underacted solutions is unable to be applied to a various array of objects. This thesis presents experimental and theoretical contributions of a novel neuro-fuzzy control method for dextrous human grasping based on grasp synergies using a Human Computer Interface glove and upgraded haptic-enabled anthropomorphic Ring Ada dexterous robotic hand. Experimental results proved the efficiency of the proposed Adaptive Neuro-Fuzzy Inference Systems to grasp objects with high levels of accuracy.

Automated grasping of objects of unknown geometry a priori has applications in many industries such as clearing a mine shaft after blasting, agricultural applications such as fruit and vegetable handling, and many roles in the service industry such as fetching items for a handicapped individual. In these roles the system environment is highly unstructured, and the robot must be able to react to different types of objects needing to be grasped. In this thesis a vision guided robotic grasp planner for unstructured environments is presented. An evaluation method for robotic grasping involving two distinct sets of objects is also presented. Both the grasp planner and evaluation metric are evaluated by experimentation using an articulated robotic arm with an eye-in-hand video camera, line laser, and pneumatic gripper. Multiple grasping experiments were performed with the objects in random poses on a modified tabletop deemed the playfield that did not allow objects to rest flat. The grasp planner focused on using a created model of the object from camera observations using silhouetting and line laser data. The object model and its computed convex hull were used to evaluate and select a single facet and point creating a grasping pair for the pneumatic gripper jaws. The grasp was attempted and then evaluated using a secondary camera and the developed evaluation method. iv Grasp success rates ranged from 80.30% (Rectangular Block on playfield 137 attempts) to 97.69% (Hexagonal Nut 173 attempts), with a mean grasp computation time for the hexagonal nut of 0.57s. / Master of Applied Science (MASc)

Hand impairments have a significant impact on quality of life and career performance. This effect is specially bold in the agricultural community, since farming activities involve continuously carrying and lifting heavy objects. Assistive robotic technologies hold considerable promise in alleviating such impairment issues. However, no portable assistive device is developed for farming applications, which requires additional considerations to ensure functionality of the device and its practicality in agricultural settings. In this work, a bi-layered structure for a robotic glove is presented, which consists of a passive extension and an active flexion layers. The former is responsible for extending the fingers, using a set of elastic bands. The flexion layer, which helps with flexing the fingers and grasping of objects, is a lightweight, self-contained, portable, cable-driven, and single-actuated robotic glove. The cable configuration is inspired from the human hand flexor tendons. Due to uncertainties associated with the fabric's flexibility and potential slippage between the cable and the glove, the designed mechanisms and sensory and control systems are initially implemented on a robotic hand. The rigid structure of the robotic hand provides a suitable proving ground for the design and control ideas. The novel power transmission system design enables the active layer to perform adaptive grasp of objects with unknown shapes, sizes, and material textures. The sensory system includes a bend sensor to detect the wearer's intention to perform grasp or release actions. Additionally, a PVDF-based sensor is developed for slip-detection, which is used as feedback to prevent further slipping of the grasped objects. Overall, the active flexion layer weighs 265 gr and can provide the maximum grasping force of 122 N, which is a noticeable improvement in comparison to the literature. / Doctor of Philosophy / Hand impairments have a significant impact on quality of life and career performance. This effect is specially bold in the agricultural community, since farming activities involve continuously carrying and lifting heavy objects. Assistive robotic technologies hold considerable promise in alleviating such impairment issues. However, no portable assistive device is developed for farming applications, which requires additional considerations to ensure functionality of the device and its practicality in agricultural settings. In this work, a bi-layered structure for a robotic glove is presented, which helps with grasping objects. The first layer is responsible for extending the fingers, using a set of elastic bands. The second layer, which helps with flexing the fingers, is a lightweight, self-contained, and portable robotic glove. A novel cable-driven power transmission system is designed to perform reliable grasps using only one actuator. The power transmission system design enables the robotic glove to grasp objects with unknown shapes, sizes, and material textures. The intention of the wearer for performing a grasp or releasing an object is detected using a bend sensor. Additionally, a vibration sensor is utilized for detecting the slip of the grasped object and preventing further slipping and dropping the object. The functionality of the developed robotic gloved is evaluated through experiments, where different geometry and weight of objects are grasped.

O problema de agrupamento de dados em grafos consiste em encontrar clusters de nós em um dado grafo, ou seja, encontrar subgrafos com alta conectividade. Esse problema pode receber outras nomenclaturas, algumas delas são: problema de particionamento de grafos e problema de detecção de comunidades. Para modelar esse problema, existem diversas formulações matemáticas, cada qual com suas vantagens e desvantagens. A maioria dessas formulações tem como desvantagem a necessidade da definição prévia do número de grupos que se deseja obter. Entretanto, esse tipo de informação não está contida em dados para agrupamento, ou seja, em dados não rotulados. Esse foi um dos motivos da popularização nas últimas décadas da medida conhecida como modularidade, que tem sido maximizada para encontrar partições em grafos. Essa formulação, além de não exigir a definição prévia do número de clusters, se destaca pela qualidade das partições que ela fornece. Nesta Tese, metaheurísticas Greedy Randomized Search Procedures para dois modelos existentes para agrupamento em grafos foram propostas: uma para o problema de maximização da modularidade e a outra para o problema de maximização da similaridade intra-cluster. Os resultados obtidos por essas metaheurísticas foram melhores quando comparadas àqueles de outras heurísticas encontradas na literatura. Entretanto, o custo computacional foi alto, principalmente o da metaheurística para o modelo de maximização da modularidade. Com o passar dos anos, estudos revelaram que a formulação que maximiza a modularidade das partições possui algumas limitações. A fim de promover uma alternativa à altura do modelo de maximização da modularidade, esta Tese propõe novas formulações matemáticas de agrupamento em grafos com e sem pesos que visam encontrar partições cujos clusters apresentem alta conectividade. Além disso, as formulações propostas são capazes de prover partições sem a necessidade de definição prévia do número de clusters. Testes com centenas de grafos com pesos comprovaram a eficiência dos modelos propostos. Comparando as partições provenientes de todos os modelos estudados nesta Tese, foram observados melhores resultados em uma das novas formulações propostas, que encontrou partições bastante satisfatórias, superiores às outras existentes, até mesmo para a de maximização de modularidade. Os resultados apresentaram alta correlação com a classificação real dos dados simulados e reais, sendo esses últimos, em sua maioria, de origem biológica / Graph clustering aims at identifying highly connected groups or clusters of nodes of a graph. This problem can assume others nomenclatures, such as: graph partitioning problem and community detection problem. There are many mathematical formulations to model this problem, each one with advantages and disadvantages. Most of these formulations have the disadvantage of requiring the definition of the number of clusters in the final partition. Nevertheless, this type of information is not found in graphs for clustering, i.e., whose data are unlabeled. This is one of the reasons for the popularization in the last decades of the measure known as modularity, which is being maximized to find graph partitions. This formulation does not require the definition of the number of clusters of the partitions to be produced, and produces high quality partitions. In this Thesis, Greedy Randomized Search Procedures metaheuristics for two existing graph clustering mathematical formulations are proposed: one for the maximization of the partition modularity and the other for the maximization of the intra-cluster similarity. The results obtained by these proposed metaheuristics outperformed the results from other heuristics found in the literature. However, their computational cost was high, mainly for the metaheuristic for the maximization of modularity model. Along the years, researches revealed that the formulation that maximizes the modularity of the partitions has some limitations. In order to promote a good alternative for the maximization of the partition modularity model, this Thesis proposed new mathematical formulations for graph clustering for weighted and unweighted graphs, aiming at finding partitions with high connectivity clusters. Furthermore, the proposed formulations are able to provide partitions without a previous definition of the true number of clusters. Computational tests with hundreds of weighted graphs confirmed the efficiency of the proposed models. Comparing the partitions from all studied formulations in this Thesis, it was possible to observe that the proposed formulations presented better results, even better than the maximization of partition modularity. These results are characterized by satisfactory partitions with high correlation with the true classification for the simulated and real data (mostly biological)