De-Sign Environment Landscape City Atti

La VI Conferenza Internazionale sul Disegno, De_Sign Environment Landscape City_Genova 2020 tratta di: Rilievo e Rappresentazione dell’Architettura e dell’Ambiente; Il Disegno per il paesaggio; Disegni per il Progetto: tracce - visioni e pre-visioni; I margini i segni della memoria e la città in progress; Cultura visiva e comunicazione dall’idea al progetto; Le emergenze architettoniche; Il colore e l’ambiente; Percezione e identità territoriale; Patrimonio iconografico culturale paesaggistico: arte, letteratura e ricadute progettuali; Segni e Disegni per il Design e Rappresentazione avanzata. Federico Babina, architetto e graphic designer presenta ARCHIVISION, e Eduardo Carazo Lefort, Docente dell’Università di Valladolid e Targa d’Oro dell’Unione Italiana Disegno la Lectio Magistralis. The VI International Conference on Drawing, De_Sign Environment Landscape City_Genoa 2020, deals with: Survey and Representation of Architecture and the Environment; Drawing for the landscape; De-signs for the Project: traces-visions and previews; Margins, signs of memory and the city in progress; Visual culture and communication from idea to project; Architectural emergencies; The color and the environment; Perception and territorial identity; Landscape cultural iconographic heritage: art, literature and design implications; Signs and Drawings for Design and Advanced Representation. Federico Babina, architect and graphic designer presents ARCHIVISION, and Professor Eduardo Carazo Lefort-University of Valladolid and Gold Plate of the Italian Design Union presents his Lectio Magistralis

Development of an adaptive navigation system for indoor mobile handling and manipulation platforms

A fundamental technology enabling the autonomous behavior of mobile robotics is navigation. It is a main prerequisite for mobile robotics to fulfill high-level tasks such as handling and manipulation, and is often identified as one of the key challenges in mobile robotics. The mapping and localization as the basis for navigation are intensively researched in the last few decades. However, there are still challenges or problems needed to be solved for online operating in large-scale environments or running on low-cost and energy-saving embedded systems. In this work, new developments and usages of Light Detection And Ranging (LiDAR) based Simultaneous Localization And Mapping (SLAM) algorithms are presented. A key component of LiDAR based SLAM algorithms, the scan matching algorithm, is explored. Different scan matching algorithms are systemically experimented with different LiDARs for indoor home-like environments for the first time. The influence of properties of LiDARs in scan matching algorithms is quantitatively analyzed. Improvements to Bayes filter based and graph optimization based SLAMs are presented. The Bayes filter based SLAMs mainly use the current sensor information to find the best estimation. A new efficient implementation of Rao-Blackwellized Particle Filter based SLAM is presented. It is based on a pre-computed lookup table and the parallelization of the particle updating. The new implementation runs efficiently on recent multi-core embedded systems that fulfill low cost and energy efficiency requirements. In contrast to Bayes filter based methods, graph optimization based SLAMs utilize all the sensor information and minimize the total error in the system. A new real-time graph building model and a robust integrated Graph SLAM solution are presented. The improvements include the definition of unique direction norms for points or lines extracted from scans, an efficient loop closure detection algorithm, and a parallel and adaptive implementation. The developed algorithm outperforms the state-of-the-art algorithms in processing time and robustness especially in large-scale environments using embedded systems instead of high-end computation devices. The results of the work can be used to improve the navigation system of indoor autonomous robots, like domestic environments and intra-logistics.Eine der grundlegenden Funktionen, welche die Autonomie in der mobilen Robotik ermöglicht, ist die Navigation. Sie ist eine wesentliche Voraussetzung dafür, dass mobile Roboter selbständig anspruchsvolle Aufgaben erfüllen können. Die Umsetzung der Navigation wird dabei oft als eine der wichtigsten Herausforderungen identifiziert. Die Kartenerstellung und Lokalisierung als Grundlage für die Navigation wurde in den letzten Jahrzehnten intensiv erforscht. Es existieren jedoch immer noch eine Reihe von Problemen, z.B. die Anwendung auf große Areale oder bei der Umsetzung auf kostengünstigen und energiesparenden Embedded-Systemen. Diese Arbeit stellt neue Ansätze und Lösungen im Bereich der LiDAR-basierten simultanen Positionsbestimmung und Kartenerstellung (SLAM) vor. Eine Schlüsselkomponente der LiDAR-basierten SLAM, die so genannten Scan-Matching-Algorithmen, wird näher untersucht. Verschiedene Scan-Matching-Algorithmen werden zum ersten Mal systematisch mit verschiedenen LiDARs für den Innenbereich getestet. Der Einfluss von LiDARs auf die Eigenschaften der Algorithmen wird quantitativ analysiert. Verbesserungen an Bayes-filterbasierten und graphoptimierten SLAMs werden in dieser Arbeit vorgestellt. Bayes-filterbasierte SLAMs verwenden hauptsächlich die aktuellen Sensorinformationen, um die beste Schätzung zu finden. Eine neue effiziente Implementierung des auf Partikel-Filter basierenden SLAM unter der Verwendung einer Lookup-Tabelle und der Parallelisierung wird vorgestellt. Die neue Implementierung kann effizient auf aktuellen Embedded-Systemen laufen. Im Gegensatz dazu verwenden Graph-SLAMs alle Sensorinformationen und minimieren den Gesamtfehler im System. Ein neues Echtzeitmodel für die Grafenerstellung und eine robuste integrierte SLAM-Lösung werden vorgestellt. Die Verbesserungen umfassen die Definition von eindeutigen Richtungsnormen für Scan, effiziente Algorithmen zur Erkennung von Loop Closures und eine parallele und adaptive Implementierung. Der entwickelte und auf eingebetteten Systemen eingesetzte Algorithmus übertrifft die aktuellen Algorithmen in Geschwindigkeit und Robustheit, insbesondere für große Areale. Die Ergebnisse der Arbeit können für die Verbesserung der Navigation von autonomen Robotern im Innenbereich, häuslichen Umfeld sowie der Intra-Logistik genutzt werden

Factors Influencing Customer Satisfaction towards E-shopping in Malaysia

Online shopping or e-shopping has changed the world of business and quite a few people have decided to work with these features. What their primary concerns precisely and the responses from the globalisation are the competency of incorporation while doing their businesses. E-shopping has also increased substantially in Malaysia in recent years. The rapid increase in the e-commerce industry in Malaysia has created the demand to emphasize on how to increase customer satisfaction while operating in the e-retailing environment. It is very important that customers are satisfied with the website, or else, they would not return. Therefore, a crucial fact to look into is that companies must ensure that their customers are satisfied with their purchases that are really essential from the ecommerce’s point of view. With is in mind, this study aimed at investigating customer satisfaction towards e-shopping in Malaysia. A total of 400 questionnaires were distributed among students randomly selected from various public and private universities located within Klang valley area. Total 369 questionnaires were returned, out of which 341 questionnaires were found usable for further analysis. Finally, SEM was employed to test the hypotheses. This study found that customer satisfaction towards e-shopping in Malaysia is to a great extent influenced by ease of use, trust, design of the website, online security and e-service quality. Finally, recommendations and future study direction is provided. Keywords: E-shopping, Customer satisfaction, Trust, Online security, E-service quality, Malaysia

Comparativa de estrategias de SLAM visual en sistemas empotrados de bajo coste

En este proyecto se pretende evaluar la posibilidad de implementar un sistema empotrado de SLAM visual a partir de la cámara de Intel ZR300, la placa de desarrollo UDOO y comparar el comportamiento de dos bibliotecas de SLAM con opción de integración en ROS, ORBSLAM2 y RTAB-Map.This project aims to evaluate the possibility of accomplish an embedded visual SLAM system from the Intel ZR300 camera, the UDOO development board and to compare the behaviour of two SLAM libraries with the option of integration in ROS, ORBSLAM2 y RTAB-Map.Grado en Ingeniería en Electrónica y Automática Industria

Design program för Kombolcha Campus

The objective for this Masters thesis is to conduct a Design program, as a planning and design tool, for the outdoor environment at the campus site of Wollo University in Kombolcha, located in northern Ethiopia. The geographical location as well as the social and political context of the site has constituted the framework for this Design program and Masters thesis. Kombolcha Campus site was established during 2006/2007, as part of the Ethiopian government’s strategy for higher development which was initiated in the Ethiopian policy of ‘Education and training’ 2001. Investment in higher education was a step towards the development of socio-economic conditions and an essential prerequisite for poverty reduction and important for the future of Ethiopia (Federal ministry of Education, 2010). The strategy has resulted in several universities being built during the last decade distributed in different parts of Ethiopia. At Kombolcha Campus, most buildings are more or less constructed. However, there are still some facilities and constructions lacking and parts of the infrastructure as well as the outdoor environment are yet to be planned, built and established. Because of its location, Kombolcha Campus confronts a high risk of flooding during heavy rainfall in the summer. There is a gully running down the hillside through the middle of the campus site which creates a threat towards many buildings and has already caused severe damage to some. In addition the campus faces problems with erosion. The outdoor environment and the vegetation at site is young and represents a surface with a few green spots and many empty, large scale, areas. It lacks seating areas and shade in order to support the use of the outdoor environment. The choice of subject for this Masters thesis was initiated from a raised interest and a request from Wollo University in order to conduct a Design program for the outdoor environment. The main focus in this Masters thesis is to highlight the landscape architectural perspectives and to contribute with a planning tool, as well as applicable design approaches. The aim is to provide additional support and ideas for the development of the outdoor environment at site. Focus has been laid upon how to strengthen the study environment and make Kombolcha Campus functioning and attractive. The emphasis has been placed on students and their desire and requirements in particular. The methods used hazve been based on a pragmatic and an empirical perspective (Patel and Davidson, 2003). Analysis tools employed have mainly been mapping, observations, participation, talks and interviews with a focus on the students in particular. Within the program special focus has been laid on how to deal with three main fields at site: Water, Vegetation and Placemaking. Examples/Suggestions of solutions are given through several approaches of how to deal with: Water issues such as flooding and erosion; possible ways to work with and establish Vegetation; as well as identification of areas suitable for additional support for Placemaking. Thereafter seven key areas are shown as examples, including a range of different approaches applied within each key area

Stereo Visual SLAM for Mobile Robots Navigation

Esta tesis está enfocada a la combinación de los campos de la robótica móvil y la visión por computador, con el objetivo de desarrollar métodos que permitan a un robot móvil localizarse dentro de su entorno mientras construye un mapa del mismo, utilizando como única entrada un conjunto de imágenes. Este problema se denomina SLAM visual (por las siglas en inglés de "Simultaneous Localization And Mapping") y es un tema que aún continúa abierto a pesar del gran esfuerzo investigador realizado en los últimos años. En concreto, en esta tesis utilizamos cámaras estéreo para capturar, simultáneamente, dos imágenes desde posiciones ligeramente diferentes, proporcionando así información 3D de forma directa. De entre los problemas de localización de robots, en esta tesis abordamos dos de ellos: el seguimiento de robots y la localización y mapeado simultáneo (o SLAM). El primero de ellos no tiene en cuenta el mapa del entorno sino que calcula la trayectoria del robot mediante la composición incremental de las estimaciones de su movimiento entre instantes de tiempo consecutivos. Cuando se usan imágenes para calcular esta trayectoria, el problema toma el nombre de "odometría visual", y su resolución es más sencilla que la del SLAM visual. De hecho, a menudo se integra como parte de un sistema de SLAM completo. Esta tesis contribuye con la propuesta de dos sistemas de odometría visual. Uno de ellos está basado en un solución cerrada y eficiente mientras que el otro está basado en un proceso de optimización no-lineal que implementa un nuevo método de detección y eliminación rápida de espurios. Los métodos de SLAM, por su parte, también abordan la construcción de un mapa del entorno con el objetivo de mejorar sensiblemente la localización del robot, evitando de esta forma la acumulación de error en la que incurre la odometría visual. Además, el mapa construido puede ser empleado para hacer frente a situaciones exigentes como la recuperación de la localización tras la pérdida del robot o realizar localización global. En esta tesis se presentan dos sistemas completos de SLAM visual. Uno de ellos se ha implementado dentro del marco de los filtros probabilísticos no parámetricos, mientras que el otro está basado en un método nuevo de "bundle adjustment" relativo que ha sido integrado con algunas técnicas recientes de visión por computador. Otra contribución de esta tesis es la publicación de dos colecciones de datos que contienen imágenes estéreo capturadas en entornos urbanos sin modificar, así como una estimación del camino real del robot basada en GPS (denominada "ground truth"). Estas colecciones sirven como banco de pruebas para validar métodos de odometría y SLAM visual

Cartographie, localisation et planification simultanées ‘en ligne’, à long terme et à grande échelle pour robot mobile

Pour être en mesure de naviguer dans des endroits inconnus et non structurés, un robot doit pouvoir cartographier l’environnement afin de s’y localiser. Ce problème est connu sous le nom de cartographie et localisation simultanées (ou SLAM pour Simultaneous Localization and Mapping). Une fois la carte de l’environnement créée, des tâches requérant un déplacement d’un endroit connu à un autre peuvent ainsi être planifiées. La charge de calcul du SLAM est dépendante de la grandeur de la carte. Un robot a une puissance de calcul embarquée limitée pour arriver à traiter l’information ‘en ligne’, c’est-à-dire à bord du robot avec un temps de traitement des données moins long que le temps d’acquisition des données ou le temps maximal permis de mise à jour de la carte. La navigation du robot tout en faisant le SLAM est donc limitée par la taille de l’environnement à cartographier. Pour résoudre cette problématique, l’objectif est de développer un algorithme de SPLAM (Simultaneous Planning Localization and Mapping) permettant la navigation peu importe la taille de l’environment. Pour gérer efficacement la charge de calcul de cet algorithme, la mémoire du robot est divisée en une mémoire de travail et une mémoire à long terme. Lorsque la contrainte de traitement ‘en ligne’ est atteinte, les endroits vus les moins souvent et qui ne sont pas utiles pour la navigation sont transférées de la mémoire de travail à la mémoire à long terme. Les endroits transférés dans la mémoire à long terme ne sont plus utilisés pour la navigation. Cependant, ces endroits transférés peuvent être récupérées de la mémoire à long terme à la mémoire de travail lorsque le le robot s’approche d’un endroit voisin encore dans la mémoire de travail. Le robot peut ainsi se rappeler incrémentalement d’une partie de l’environment a priori oubliée afin de pouvoir s’y localiser pour le suivi de trajectoire. L’algorithme, nommé RTAB-Map, a été testé sur le robot AZIMUT-3 dans une première expérience de cartographie sur cinq sessions indépendantes, afin d’évaluer la capacité du système à fusionner plusieurs cartes ‘en ligne’. La seconde expérience, avec le même robot utilisé lors de onze sessions totalisant 8 heures de déplacement, a permis d’évaluer la capacité du robot de naviguer de façon autonome tout en faisant du SLAM et planifier des trajectoires continuellement sur une longue période en respectant la contrainte de traitement ‘en ligne’ . Enfin, RTAB-Map est comparé à d’autres systèmes de SLAM sur quatre ensembles de données populaires pour des applications de voiture autonome (KITTI), balayage à la main avec une caméra RGB-D (TUM RGB-D), de drone (EuRoC) et de navigation intérieur avec un robot PR2 (MIT Stata Center). Les résultats montrent que RTAB-Map peut être utilisé sur de longue période de temps en navigation autonome tout en respectant la contrainte de traitement ‘en ligne’ et avec une qualité de carte comparable aux approches de l’état de l’art en SLAM visuel et avec télémètre laser. ll en résulte d’un logiciel libre déployé dans une multitude d’applications allant des robots mobiles intérieurs peu coûteux aux voitures autonomes, en passant par les drones et la modélisation 3D de l’intérieur d’une maison

Library buildings around the world

"Library Buildings around the World" is a survey based on researches of several years. The objective was to gather library buildings on an international level starting with 1990

Personalized Medicine, in Relation to Redox State, Diet and Lifestyle

“Personalized Medicine, in Relation to Redox State, Diet and Lifestyle” is a book on the important issues regarding good health and a need for more selective and sensitive systems to identify diseases. It is a complex issue. Presently, in 2020 we have the fight against Coronavirus with high lethality and the world is asking for information on its metabolism, spread and tools to prevent, protect and cure. The complexity of diseases indicate that we must involve diet and lifestyle at the individual level and discuss the possible impact on evolutionary defense systems. We also need to include discussions of the redox state of compounds and this requires collaborations between research areas. The book has gathered interdisciplinary works, joining fields such as trace elements, biochemistry, physiology and analytical chemistry with the aim of finding new approaches to diseases, for example by using individual treatment at the cellular level