A Robust Localization System for Inspection Robots in Sewer Networks †

Sewers represent a very important infrastructure of cities whose state should be monitored periodically. However, the length of such infrastructure prevents sensor networks from being applicable. In this paper, we present a mobile platform (SIAR) designed to inspect the sewer network. It is capable of sensing gas concentrations and detecting failures in the network such as cracks and holes in the floor and walls or zones were the water is not flowing. These alarms should be precisely geo-localized to allow the operators performing the required correcting measures. To this end, this paper presents a robust localization system for global pose estimation on sewers. It makes use of prior information of the sewer network, including its topology, the different cross sections traversed and the position of some elements such as manholes. The system is based on a Monte Carlo Localization system that fuses wheel and RGB-D odometry for the prediction stage. The update step takes into account the sewer network topology for discarding wrong hypotheses. Additionally, the localization is further refined with novel updating steps proposed in this paper which are activated whenever a discrete element in the sewer network is detected or the relative orientation of the robot over the sewer gallery could be estimated. Each part of the system has been validated with real data obtained from the sewers of Barcelona. The whole system is able to obtain median localization errors in the order of one meter in all cases. Finally, the paper also includes comparisons with state-of-the-art Simultaneous Localization and Mapping (SLAM) systems that demonstrate the convenience of the approach.Unión Europea ECHORD ++ 601116Ministerio de Ciencia, Innovación y Universidades de España RTI2018-100847-B-C2

Internet QoS for DiffServ-Enabled Routers

Differentiated Service Model (DiffServ) is currently a popular research topic as a low-cost method to bring QoS to today's Internet backbone network. In this paper, the author introduces the techniques and methodologies that used to design and implement DiffServ-enabled (DS-enabled) routers. The adaptations of DS-enabled routers are designed to cater to the low Internet connectivity within Universiti Teknologi PETRONAS LAN. The author has implemented basic DiffServ setting using three CISC03725 routers. Based on these DiffServ-enabled routers, the author set up a small scale lab network to study DiffServ QoS features: priority dropping (discrimination among different service classes), QoS guarantees and measuring QoS using various formal metrics (delay and throughput). Furthermore, the author present problems encountered during study, and the proposed solutions

PROPOSED MIDDLEWARE SOLUTION FOR RESOURCE-CONSTRAINED DISTRIBUTED EMBEDDED NETWORKS

The explosion in processing power of embedded systems has enabled distributed embedded networks to perform more complicated tasks. Middleware are sets of encapsulations of common and network/operating system-specific functionality into generic, reusable frameworks to manage such distributed networks. This thesis will survey and categorize popular middleware implementations into three adapted layers: host-infrastructure, distribution, and common services. This thesis will then apply a quantitative approach to grading and proposing a single middleware solution from all layers for two target platforms: CubeSats and autonomous unmanned aerial vehicles (UAVs). CubeSats are 10x10x10cm nanosatellites that are popular university-level space missions, and impose power and volume constraints. Autonomous UAVs are similarly-popular hobbyist-level vehicles that exhibit similar power and volume constraints. The MAVLink middleware from the host-infrastructure layer is proposed as the middleware to manage the distributed embedded networks powering these platforms in future projects. Finally, this thesis presents a performance analysis on MAVLink managing the ARM Cortex-M 32-bit processors that power the target platforms

Improving software quality using an ontology-based approach

Ensuring quality in software development is a challenging process. The concepts of anti-pattern and bad code smells utilize the knowledge of reoccurring problems to improve the quality of current and future software development. Anti-patterns describe recurring bad design solutions while bad code smells describe source code that is error-free but difficult to understand and maintain. Code refactoring aims to remove bad code smells without changing a program’s functionality while improving program quality. There are metrics-based tools to detect a few bad code smells from source code; however, the knowledge and understanding of these indicators of low quality software are still insufficient to resolve many of the problems they represent. Minimal research addresses the relationships between or among bad code smells, anti-patterns and refactoring. In this research, we present a new ontology, Ontology for Anti-patterns, Bad Code Smells and Refactoring (OABR), to define the concepts and their relation properties. Such an ontological infrastructure encourages a common understanding of these concepts among the software community and provides more concise definitions that help to avoid overlapping and inconsistent description. It utilizes reasoning capabilities associated with ontology to analyze the software development domain and offer new insights into the domain. Software quality issues such as understandability and maintainability can be improved by identifying and resolving anti-patterns associated with code smells as well as preventing bad code smells before coding begins

Automatic target recognition based on cross-plot

Automatic target recognition that relies on rapid feature extraction of real-time target from photo-realistic imaging will enable efficient identification of target patterns. To achieve this objective, Cross-plots of binary patterns are explored as potential signatures for the observed target by high-speed capture of the crucial spatial features using minimal computational resources. Target recognition was implemented based on the proposed pattern recognition concept and tested rigorously for its precision and recall performance. We conclude that Cross-plotting is able to produce a digital fingerprint of a target that correlates efficiently and effectively to signatures of patterns having its identity in a target repository.Kelvin Kian Loong Wong and Derek Abbot

PS Poster Session - All

This document includes all poster sessions at the IBPC 2018

Simultaneous Variable and Covariance Selection with the Multivariate Spike-and-Slab Lasso

We propose a Bayesian procedure for simultaneous variable and covariance selection using continuous spike-and-slab priors in multivariate linear regression models where q possibly correlated responses are regressed onto p predictors. Rather than relying on a stochastic search through the high-dimensional model space, we develop an ECM algorithm similar to the EMVS procedure of Rockova & George (2014) targeting modal estimates of the matrix of regression coefficients and residual precision matrix. Varying the scale of the continuous spike densities facilitates dynamic posterior exploration and allows us to filter out negligible regression coefficients and partial covariances gradually. Our method is seen to substantially outperform regularization competitors on simulated data. We demonstrate our method with a re-examination of data from a recent observational study of the effect of playing high school football on several later-life cognition, psychological, and socio-economic outcomes

Fiabilité de l’underfill et estimation de la durée de vie d’assemblages microélectroniques

Abstract : In order to protect the interconnections in flip-chip packages, an underfill material layer is used to fill the volumes and provide mechanical support between the silicon chip and the substrate. Due to the chip corner geometry and the mismatch of coefficient of thermal expansion (CTE), the underfill suffers from a stress concentration at the chip corners when the temperature is lower than the curing temperature. This stress concentration leads to subsequent mechanical failures in flip-chip packages, such as chip-underfill interfacial delamination and underfill cracking. Local stresses and strains are the most important parameters for understanding the mechanism of underfill failures. As a result, the industry currently relies on the finite element method (FEM) to calculate the stress components, but the FEM may not be accurate enough compared to the actual stresses in underfill. FEM simulations require a careful consideration of important geometrical details and material properties. This thesis proposes a modeling approach that can accurately estimate the underfill delamination areas and crack trajectories, with the following three objectives. The first objective was to develop an experimental technique capable of measuring underfill deformations around the chip corner region. This technique combined confocal microscopy and the digital image correlation (DIC) method to enable tri-dimensional strain measurements at different temperatures, and was named the confocal-DIC technique. This techique was first validated by a theoretical analysis on thermal strains. In a test component similar to a flip-chip package, the strain distribution obtained by the FEM model was in good agreement with the results measured by the confocal-DIC technique, with relative errors less than 20% at chip corners. Then, the second objective was to measure the strain near a crack in underfills. Artificial cracks with lengths of 160 μm and 640 μm were fabricated from the chip corner along the 45° diagonal direction. The confocal-DIC-measured maximum hoop strains and first principal strains were located at the crack front area for both the 160 μm and 640 μm cracks. A crack model was developed using the extended finite element method (XFEM), and the strain distribution in the simulation had the same trend as the experimental results. The distribution of hoop strains were in good agreement with the measured values, when the model element size was smaller than 22 μm to capture the strong strain gradient near the crack tip. The third objective was to propose a modeling approach for underfill delamination and cracking with the effects of manufacturing variables. A deep thermal cycling test was performed on 13 test cells to obtain the reference chip-underfill delamination areas and crack profiles. An artificial neural network (ANN) was trained to relate the effects of manufacturing variables and the number of cycles to first delamination of each cell. The predicted numbers of cycles for all 6 cells in the test dataset were located in the intervals of experimental observations. The growth of delamination was carried out on FEM by evaluating the strain energy amplitude at the interface elements between the chip and underfill. For 5 out of 6 cells in validation, the delamination growth model was consistent with the experimental observations. The cracks in bulk underfill were modelled by XFEM without predefined paths. The directions of edge cracks were in good agreement with the experimental observations, with an error of less than 2.5°. This approach met the goal of the thesis of estimating the underfill initial delamination, areas of delamination and crack paths in actual industrial flip-chip assemblies.Afin de protéger les interconnexions dans les assemblages, une couche de matériau d’underfill est utilisée pour remplir le volume et fournir un support mécanique entre la puce de silicium et le substrat. En raison de la géométrie du coin de puce et de l’écart du coefficient de dilatation thermique (CTE), l’underfill souffre d’une concentration de contraintes dans les coins lorsque la température est inférieure à la température de cuisson. Cette concentration de contraintes conduit à des défaillances mécaniques dans les encapsulations de flip-chip, telles que la délamination interfaciale puce-underfill et la fissuration d’underfill. Les contraintes et déformations locales sont les paramètres les plus importants pour comprendre le mécanisme des ruptures de l’underfill. En conséquent, l’industrie utilise actuellement la méthode des éléments finis (EF) pour calculer les composantes de la contrainte, qui ne sont pas assez précises par rapport aux contraintes actuelles dans l’underfill. Ces simulations nécessitent un examen minutieux de détails géométriques importants et des propriétés des matériaux. Cette thèse vise à proposer une approche de modélisation permettant d’estimer avec précision les zones de délamination et les trajectoires des fissures dans l’underfill, avec les trois objectifs suivants. Le premier objectif est de mettre au point une technique expérimentale capable de mesurer la déformation de l’underfill dans la région du coin de puce. Cette technique, combine la microscopie confocale et la méthode de corrélation des images numériques (DIC) pour permettre des mesures tridimensionnelles des déformations à différentes températures, et a été nommée le technique confocale-DIC. Cette technique a d’abord été validée par une analyse théorique en déformation thermique. Dans un échantillon similaire à un flip-chip, la distribution de la déformation obtenues par le modèle EF était en bon accord avec les résultats de la technique confocal-DIC, avec des erreurs relatives inférieures à 20% au coin de puce. Ensuite, le second objectif est de mesurer la déformation autour d’une fissure dans l’underfill. Des fissures artificielles d’une longueuer de 160 μm et 640 μm ont été fabriquées dans l’underfill vers la direction diagonale de 45°. Les déformations circonférentielles maximales et principale maximale étaient situées aux pointes des fissures correspondantes. Un modèle de fissure a été développé en utilisant la méthode des éléments finis étendue (XFEM), et la distribution des contraintes dans la simuation a montré la même tendance que les résultats expérimentaux. La distribution des déformations circonférentielles maximales était en bon accord avec les valeurs mesurées lorsque la taille des éléments était plus petite que 22 μm, assez petit pour capturer le grand gradient de déformation près de la pointe de fissure. Le troisième objectif était d’apporter une approche de modélisation de la délamination et de la fissuration de l’underfill avec les effets des variables de fabrication. Un test de cyclage thermique a d’abord été effectué sur 13 cellules pour obtenir les zones délaminées entre la puce et l’underfill, et les profils de fissures dans l’underfill, comme référence. Un réseau neuronal artificiel (ANN) a été formé pour établir une liaison entre les effets des variables de fabrication et le nombre de cycles à la délamination pour chaque cellule. Les nombres de cycles prédits pour les 6 cellules de l’ensemble de test étaient situés dans les intervalles d’observations expérimentaux. La croissance de la délamination a été réalisée par l’EF en évaluant l’énergie de la déformation au niveau des éléments interfaciaux entre la puce et l’underfill. Pour 5 des 6 cellules de la validation, le modèle de croissance du délaminage était conforme aux observations expérimentales. Les fissures dans l’underfill ont été modélisées par XFEM sans chemins prédéfinis. Les directions des fissures de bord étaient en bon accord avec les observations expérimentales, avec une erreur inférieure à 2,5°. Cette approche a répondu à la problématique qui consiste à estimer l’initiation des délamination, les zones de délamination et les trajectoires de fissures dans l’underfill pour des flip-chips industriels

Exploring protein fitness landscapes with new high-throughput technologies

The concept of a protein’s fitness landscape – an abstract space in which related sequences are close together and matched with their fitness – is a useful tool to visualize core principles of protein evolution. Acquiring a new function, for example the laboratory evolution of an enzyme to convert an industrially relevant substrate, can be understood as a stepwise climb through a fitness landscape, reaching higher fitness (or activity) with each step (or mutation). The valleys of such a space relate to the starting points of protein engineering campaigns. Understanding this area could enlighten principles of how proteins quickly adapt in nature and help to identify starting points with a high potential for evolution, a high ‘evolvability’, speeding up protein engineering. In this study, high-throughput technologies will be developed that enable the read-out of directed evolution on a large scale, tracking the exploration of the valley of a fitness landscape: the conversion of an amino acid- to amine dehydrogenase will be investigated as a model of enzyme evolvability with a drastic change of substrate specificity. A sensitive high-throughput screening assay as well as a comprehensive sequencing read-out will be required to establish the identity of selected variants during evolution. I will first generate and characterize three different but related starting points and test their initial evolvability. Stabilizing the starting point results in increased mutational robustness, broadening the range of accepted mutations. However, increased initial stability does not necessarily correlate to higher functional improvement, hinting at a nuanced view of evolvability. A sensitive high-throughput assay is necessary to verify the full potential of the starting points and study the early steps of evolution comprehensively. Broadly applicable ultrahigh-throughput assays of enzyme function, such as absorbance-activated droplet sorting, currently lack the sensitivity of more specific fluorescence-based or low-throughput counterparts. A universal approach to increase detectability in single cell-lysate microfluidic enzyme assays is established by amplifying the enzyme content per droplet more than 10-fold via homogeneous clonal cell growth. Clonal amplification enables the sensitive and precise detection of newly introduced amine dehydrogenase activities, a feat restricted in conventional assays by low initial activity and stability. To generate a truly complete view of directed evolution in a fitness landscape, however, an equally powerful sequencing read-out is necessary to identify all selected variants. Here, unique molecular identifiers are used to increase the accuracy of nanopore sequencing to levels that can reliably distinguish point mutations. I establish an inexpensive and straightforward long read amplicon sequencing workflow which is then applied to map the trajectories of two comparative long-term directed evolution campaigns. In the parallel evolution campaigns, initial beneficial mutations are exclusive to each starting point and lead to incompatible trajectories. Beneficial mutations are scarce and large improvements are unavailable until recombination occurs and a jump through the fitness landscape is realized. The recombined variant holds high evolvability and quickly evolves to take over the population and form the most successful lineages, indicating the power of recombination as a means to innovation in protein evolution. The tools established in this thesis can help protein engineers explore fitness landscapes more economically and comprehensively. Their application to mapping full trajectories of early adaptation uncovers differences in the evolvability of homologs, potentially aiding the identification of evolvable starting points as well as strategies to increase evolvability for efficient protein engineering in the future

Event Parsing In Narrative: Trials And Tribulations Of Archaic English Fairy Tales

While event extraction and automatic summarization have taken great strides in the realm of news stories, fictional narratives like fairy tales have not been so fortunate. A number of challenges arise from the literary elements present in fairy tales that are not found in more straightforward corpora of natural language, such as archaic expressions and sentence structures. To aid in summarization of fictional texts, I created an class - a template for a digital object, in this case a semantic and story event - that captures elements predicted to help classify events as important for inclusion. I wrote a processor to run over a new corpus of fairy tales and parse them into events, then to be manually annotated for importance and clustered to create a classifier that could be used on novel texts. These two latter steps could not be completed before publication of this paper, but my proposed approach is covered extensively, as is future work along the same lines. Along with this paper, supplementary materials encompassing the event class, processor code, corpus in full text, and corpus as un-annotated event data are included