Improvement on the Wi-Fi vehicle simulator ERA

In recent years, the boom generated by the IoT is allowing many technologies to move towards automation. One of the fields taking advantage of it is autonomous driving. What we can observe is that most vehicle manufacturers are using sensor redundancy to solve the problem of erroneous detection in order to achieve secure systems. However, it is inefficient as a solution in general. One approach that has been gaining momentum in recent years is collaborative perception ("Swarm Intelligence Technologies"), where the data that sensors capture between vehicles is transmitted, gaining a general overview of the situation. So, are "Swarm Intelligence Technologies" the future? Can we check this without having to invest millions of dollars in experimental vehicles, save ourselves from doing tests in cities and thus not having to endanger pedestrians? Is a simulator a good idea? How realistic is it? What are its limitations? These are all the different questions we asked ourselves when we started this project. In order to be able to demonstrate that these technologies are more optimal in V2X communications environments, it is necessary to experiment and contrast results. At the same time, being able to do tests and get results with different scenarios without increasing the cost of experimentation is important. In this project, you will notice that it starts with a tool called ERA that allows vehicular communication in a basic simulation environment called Gazebo. However, tool is quite simple and does not present any experiment that can be translated to a vehicle and that is why it was essential to move it to a more realistic environment. If we manage to adapt to an environment as realistic as possible, from there we can create many different experiments to check how the DSRC (Dedicated Short Range Communication) behaves and whether the solutions regarding vehicle perception are efficient and good. This will drastically shorten the time needed for us to live in a safer world with reliable autonomous vehicles. This project has started with the introduction to the tools needed for project development (ROS, C ++, Unreal Engine), experimenting with the current state of the ERA tool and understanding exactly what it does and how it achieves it. Afterwards, we created a base experiment in the new Carla environment with the code that binds the ERA tool to the simulator. Finally, we switched from V2V unicast to multicast communications (much more efficient). At last, an important comment is that the project included some concepts outside the simulation scope improvement to have more tools for future experimentation such as basic object detection and Operative Systems specific for UAVs (such as drones). These can be useful to have test cases on small vehicles on the future.En estos últimos años el boom que ha generado el IoT está permitiendo que muchas tecnologías avancen hacia la automatización. Uno de los campos donde más se ha visto beneficiado es el de la conducción autónoma. Lo que vemos es que la mayoría de fabricantes de vehículos utilizan redundancia en los sensores para solucionar el problema de detecciones erróneas y tener sistemas seguros, pero es poco eficiente como solución. Un planteamiento que está ganando fuerza los últimos años es el de la colaboración perceptiva entre vehículos ( "Swarm Intelligence Technologies"), donde se transmiten los datos que los vehiculos captan entre ellos, ganando una visión global de la situación. Entonces, son las "Swarm Intelligence Technologies" el futuro? Podemos comprobarlo sin tener que invertir million de dólares en vehículos experimentales, ahorrarnos hacer tests en ciudades y así no tener que poner en peligro a los peatones? Es un simulador una buena idea? Cuánto semejante es? ¿Cuáles son las limitaciones que presenta? Todas estas son las diferentes preguntas que nos hemos planteado al comenzar este proyecto. Para poder demostrar que las estas tecnologías son más óptimas en entornos de comunicaciones V2X hay que experimentar y contrastar resultados. Al mismo tiempo, poder hacer tests y obtener resultados con diferentes escenarios sin aumentar el coste de experimentación es importante. En este proyecto, observará que parto de una herramienta llamada ERA que permite la comunicación vehicular en un entorno de simulación básico como es Gazebo. Esta herramienta es bastante simple y no presenta ninguna situación que se pueda trasladar a un vehículo y es por eso que es esencial trasladarlo a algún entorno más realista. Si conseguimos adaptarnos a un entorno lo más objetivo posible, a partir de ahí se podrán crear numerosos y diferentes experimentos para comprobar como el DSRC (Dedicated Short Range Communication) se comporta y si las soluciones respecto a la percepción vehicular son eficientes y buenas. Esto permitirá acortar drásticamente el tiempo necesario para que podamos vivir en un mundo más seguro con vehículos autónomos fiables. Este proyecto ha empezado con la introducción a las herramientas necesarias para el desarrollo del proyecto (ROS, C ++, Unreal Engine), experimentando el estado actual de la herramienta ERA y entendiendo exactamente qué hace y cómo lo consigue. Después, se ha creado un experimento base al nuevo entorno Carla y el código que une la herramienta ERA al simulador. Finalmente, se ha pasado de comunicaciones unicast V2V comunicaciones V2V multicast (mucho más eficientes). Finalmente, un comentario importante es que el proyecto ha incluido un anexo fuera del proyecto para tener más herramientas para futuros experimentos como son la detección de objetos básicos y los sistemas operativos específicos para drones. Estos, pueden ser útiles para tener casos de prueba en vehículos en el futuro.En aquests darrers anys el boom que ha generat el IoT està permetent que moltes tecnologies avancin cap a la automatització. Un dels camps on més s'ha vist beneficiat és el de la conducció autònoma. El que veiem és que la majoria de fabricants de vehicles utilitzen redundància als sensors per a solucionar el problema de deteccions errònies i tenir sistemes segurs. Malgrat això, és poc eficient com a solució en general. Un plantejament que està guanyant força els últims anys és el de la col·laboració perceptiva entre vehicles ("Swarm Intelligence Technologies"), on es transmeten les dades que els vehicles capten entre ells, guanyant una visió global de la situació. Llavors, són les "Swarm Intelligence Technologies" el futur. Podem comprovar-ho sense haver d'invertir milions de dolars en vehicles experimentals, estalviar-nos fer tests en ciutats i així no haver de posar en perill als vianants? És un simulador una bona idea? Quant de semblant és? Quines són les limitacions que presenta. Totes aquestes són les diferents preguntes que ens hem plantejat al començar aquest projecte. Per a poder demostrar que les aquestes tecnologies són més optimes en entorns de comunicacions V2X cal experimentar i contrastar resultats. Al mateix temps, poder fer tests i obtenir resultats amb diferents escenaris sense augmentar el cost d'experimentació és important. En aquest projecte, observareu que es parteix del software ERA que permet la comunicació vehicular en un entorn de simulació bàsic com és Gazebo. Malgrat això, aquesta eina és força simple i no presenta cap situació que es pugui traslladar a un vehicle i és per això que és essencial traslladar-ho a algun entorn més realista. Si aconseguim adaptar-nos a un entorn el més objectiu possible, a partir d'aquí es podran crear nombrosos i diferents experiments per a comprovar com el DSRC (Dedicated Short Range Communication) es comporta i si les solucions respecte a la percepció vehicular són eficients i bones. Això permet escurçar dràsticament el temps necessari per a que puguem viure en un món més segur amb vehicles autonòms fiables. Aquest projecte ha començat amb la introducció a les eines necessàries per al desenvolupament del projecte (ROS, C ++, Unreal Engine), experimentant l'estat actual de l'eina ERA i entenent exactament què fa i com ho aconsegueix. Després, s'ha creat un experiment base al nou entorn Carla i el codi que uneix l'eina ERA al simulador. Finalment, s'ha passat de comunicacions unicast V2V a comunicacions V2V multicast (molt més eficients). Finalment, un comentari important és que el projecte ha inclòs un annex fora del projecte per a tenir més eines per a futurs experiments com ara la detecció d'objectes bàsics i els sistemes operatius específics per als drons. Aquests, poden ser útils per tenir casos de prova en vehicles en el futur

Using clustering algorithms to characterize traffic accidents in the city of Barcelona

Road traffic accidents are a major public health concern that continues to threaten the safety of individuals worldwide. These incidents result in many injuries, disabilities, and fatalities, which not only cause immense pain and suffering to victims and their loved ones but also sig- nificantly impact society as a whole. Consequently, it could be useful to identify patterns that can help define and implement effective preventive measures. In this context, this project aims to study traffic accidents in Barcelona between 2021 and 2022, using available data from Open Data BCN. The project will apply clustering, a powerful technique that can identify patterns in data. Specif- ically, various experiments will be conducted to detect the main characteristics of the studied accidents and obtain relevant profiles. These profiles will be analyzed to prevent similar incidents in the future. The programming language used in this thesis is Python to achieve these clusters and conduct the analysis. It offers a rich set of data processing, analysis, and visualization tools, making it a highly suitable choice for the proposed project. Overall, this project aims to apply clustering to gain a deeper understanding of traffic accidents in Barcelona, with the ultimate goal of contribute to the prevention of similar incidents in the futureLos accidentes de tráfico son una preocupación importante para la salud pública que continúa amenazando la seguridad de las personas en todo el mundo. Estos incidentes resultan en muchas lesiones, discapacidades y fatalidades, lo cual no solo causa un inmenso dolor y sufrim- iento a las víctimas y sus seres queridos, sino que también impacta significativamente a la so- ciedad en su conjunto. En consecuencia, podría ser útil identificar patrones que puedan ayudar a definir e implementar medidas preventivas efectivas. En este contexto, este proyecto tiene como objetivo estudiar los accidentes de tráfico en Barcelona entre 2021 y 2022, utilizando los datos disponibles de Open Data BCN. El proyecto aplicará el "clustering", una poderosa técnica que puede identificar patrones en los datos. Específicamente, se llevarán a cabo varios experimentos para detectar las principales características de los accidentes estudiados y obtener perfiles relevantes. Estos perfiles serán analizados para prevenir incidentes similares en el futuro. El lenguaje de programación utilizado en esta tesis es Python para lograr estos grupos y llevar a cabo el análisis. Ofrece un conjunto amplio de herramientas para el procesamiento, análisis y visualización de datos, lo que lo convierte en una opción muy adecuada para el proyecto propuesto. En general, este proyecto tiene como objetivo aplicar técnicas de "clustering" para obtener una comprensión más profunda de los accidentes de tráfico en Barcelona, con el objetivo final de contribuir a la prevención de incidentes similares en el futuro.Els accidents de trànsit són una preocupació important per a la salut pública que continua ame- naçant la seguretat de les persones arreu del món. Aquests incidents provoquen moltes lesions, discapacitats i morts, la qual cosa no només causa un immens dolor i patiment a les víctimes i als seus éssers estimats, sinó que també impacta de manera significativa a la societat en el seu conjunt. En conseqüència, podria ser útil identificar patrons que puguin ajudar a definir i implementar mesures preventives efectives. En aquest context, aquest projecte té com a ob- jectiu estudiar els accidents de trànsit a Barcelona entre el 2021 i el 2022, utilitzant les dades disponibles d’Open Data BCN. El projecte aplicarà el "clustering", una tècnica potent que pot identificar patrons en les dades. Es realitzaran diversos experiments per detectar les principals característiques dels accidents estudiats i obtenir perfils rellevants. Aquests perfils seran analitzats per prevenir incidents sim- ilars en el futur. El llenguatge de programació utilitzat en aquesta tesi és Python per aconseguir aquests grups i dur a terme l’anàlisi. Ofereix un conjunt ampli d’eines per al processament, anàlisi i visualització de dades, la qual cosa el converteix en una opció molt adient per al projecte proposat. En general, aquest projecte té com a objectiu aplicar tècniques de "clustering" per obtenir una comprensió més profunda dels accidents de trànsit a Barcelona, amb l’objectiu final de con- tribuir a la prevenció d’incidents similars en el futur

The Study Of Photo-reduction Of Cerium Oxide Nanoparticles In Presence Of Dextran: An Attempt In Understanding The Functionality Of The System

Malignant melanoma cancer is the sixth common cancer diagnosed in the United States. Surgery, chemotherapy and radiation are some of the successful techniques in killing tumor cells. However, in these techniques, it is not easy to distinguish tumor cells from the healthy once which inadvertently get exposed to chemical agent/radiation. Therefore it is required to develop an anticancer agent which selectively kills the cancer cells, while still protecting the normal tissues. In our preliminary work, we have shown that Dextran (1000Da) coated Cerium oxide nanoparticles (Dex-CNPs) selectively kills the cancer cells (50% killing at a concentration of 150μM) without inducing toxicity to the normal cells. However, the mechanism involved on how CNPs/Dex-CNPs attain the selectivity and efficiently kill the tumor cells is still unknown. In this study we have synthesized Dextran coated ceria nano particles (Dex- CNPs) with different surface oxidation state ratio (Ce4+/Ce3+). This will provide an in depth understanding of the key chemical and physical properties of the system that can improve its efficacy. The varied surface oxidation of the particles is achieved by exposing Dex-CNPs to light which initiates a color change from dark to pale yellow indicating the reduction of Ce4+ to Ce3+. Interestingly we have found that the DexCNPs exposed to light have reduced cytotoxicity towards squamous cell carcinoma cell line (CCL30) compared to the protected once. Characterization of the same revealed that Dex- CNPs exposed to light have decreased Ce4+ /Ce3+ surface oxidation ratio compared to the other. This provides more insight in useful synthesis of Dex-CNPs in terms of storage and handling. In summary, higher Ce4+ /Ce3+ surface oxidation ratio is more efficient in hindering tumor growth by effectively hindering the tumor-stoma interaction

The Study of Physiochemical Properties of Cerium Oxide Nanoparticles and its Application in Biosensors

Biosensors continue to get smaller and faster with the advancement in nanotechnology through the use of nanomaterials to achieve high sensitivity and selectivity. However, the continued reliance on biomolecules or enzymes in the biosensor assembly poses the problem of reproducibility, storage and complexity. This dissertation research address some of the challenges by investigating the physiochemical properties of nanoparticles to understand its interaction with biological systems and develop enzyme free biosensors. In this study, we have demonstrated a novel strategy to integrate cerium oxide nanoparticles (CNPs) as an efficient transducer through rigorous screening for developing enzyme/label free biosensors for detecting analytes such as dopamine associated with neurodegenerative diseases and limonin for fruit quality management. CNPs have been proven to exhibit antioxidant properties attributed to its dynamic change in surface oxidation states (Ce4+ to Ce3+ and vice versa) mediated at the oxygen vacancies on the surface of the CNPs. It is also well-established that nanoparticles are resourceful novel materials with a plethora of applications in the field of nanomedicine. It is of significant importance to study the changes in physiochemical properties of different synthesized CNPs for effective use in biomedical applications. In one of the studies, the effects of different anions in the precursor of the cerium salts used for synthesizing CNPs using the same synthesis method, were extensively studied. It has been demonstrated that the physicochemical properties such as dispersion stability, hydrodynamic size, and the signature surface chemistry, antioxidant catalytic activity, oxidation potentials of different CNPs have been significantly altered with the change of anions in the precursor salts. . The increased antioxidant property of CNPs prepared using the precursor salts containing NO3¯ and Cl¯ ions have been extensively studied using in-situ UV-Visible spectroscopy which reveal that the change in oxidation potentials of CNPs with the change in concentration of anions. Thus, this work demonstrated that the physicochemical and antioxidant properties of CNPs can be tuned by anions of the precursor during the synthesis process. After standardizing the synthesis process, CNPs have been immobilized on highly ordered polymer nanopillars to develop an optical sensor for dopamine detection. Dopamine, is one of the main neurotransmitters which plays a significant role in central nervous system and its deficiency leads to neurological disorders such as Parkinson\u27s disease, schizophrenia etc. Current biosensors in the literature use invasive detection techniques and lacks sensitivity to detect physiological clinically relevant concentrations of dopamine. The interaction between CNPs and dopamine have been extensively studied using UV-visible spectro-electrochemical studies to achieve the right surface chemistry (35-70% Ce4+). The sensor exhibits high sensitivity (1fM detection in simulated body fluid), high selectivity (in acetic acid, sheep plasma) and increased robustness with several cycles of usage. Furthermore, we have developed a CNPs based biosensor by integrating it on a transistor platform for improved sensitivity and better adhesion by immobilizing in silk fibroin matrix. In the final study, CNPs integrated in silk fibroin (SF) polymer electrospun nanofibers incorporated on an organic electrochemical transistor platform, is used to develop a limonin sensor. It has been established that the concentration of limonin in citric fruit predicts the quality in terms of bitter taste from the HLB bacteria infected fruits. A unique in-house electrospinning set-up using drum as collector was used to develop SF (extracted from cocoon) nanofibers used as CNP (synthesized in-situ in fibers) transducer carrier, both of which have a specific interaction with limonin. This novel biosensor has exhibited high sensitivity (100nM in PBS) and selectivity (citric acid, sugar etc.) with improved robustness in terms of reuse. The broader impact of the study is to develop holistic diagnostic non-invasive biosensors that can directly be used to detect the analytes using samples from humans and/or on field for fruit quality determination, which is a huge stepping stone in the advancement of nanotechnology based biosensors. This will fuel future generation of enzyme free biosensors which can utilize similar concepts for the detection of other analytes. The biosensor could be printed on a flexible substrate to advance wearable smart biosensor and could eventually enable users to wirelessly monitor the analyte concentrations using smartphones

Robust co-planning of transmission expansion and merchant energy storage investments considering long- and short-term uncertainties

The decreasing cost of energy storage technologies and the increasing utilization of renewable energy sources have made distributed transmission-scale energy storage economically viable. Merchant energy storage investors can collect significant profits through spatiotemporal energy arbitrage from congested transmission lines. This paper formulates a three-stage, four-level min–min–max–min problem from the viewpoint of power system operators and planners such that they will build new transmission lines and identify potential locations for profitable merchant energy storage investments. The first level determines transmission expansion decisions from the system operator’s perspective. The second level plans potential investments in merchant energy storage to ensure profitability at a desired rate of return. The third level realizes the worst-case situations of long-term uncertainties related to the expansion of wind farms and peak load growth in each regional zone, while the fourth level simulates market clearing for representative days, modeling short-term uncertainties. A novel iterative nested column and constraint generation (C&CG) technique is adopted to cope with numerical issues caused by binary variables of transmission lines and storage blocks and the enormous size of the problem. The case study of a modified IEEE 24-bus test system was used to assess the effectiveness of the proposed algorithm

Fabricated Micro-Nano Devices For In Vivo And In Vitro Biomedical Applications

In recent years, the innovative use of microelectromechanical systems (MEMSs) and nanoelectromechanical systems (NEMSs) in biomedical applications has opened wide opportunities for precise and accurate human diagnostics and therapeutics. The introduction of nanotechnology in biomedical applications has facilitated the exact control and regulation of biological environments. This ability is derived from the small size of the devices and their multifunctional capabilities to operate at specific sites for selected durations of time. Researchers have developed wide varieties of unique and multifunctional MEMS/NEMS devices with micro and nano features for biomedical applications (BioMEMS/NEMS) using the state of the art microfabrication techniques and biocompatible materials. However, the integration of devices with the biological milieu is still a fundamental issue to be addressed. Devices often fail to operate due to loss of functionality, or generate adverse toxic effects inside the body. The in vitro and in vivo performance of implantable BioMEMS such as biosensors, smart stents, drug delivery systems, and actuation systems are researched extensively to understand the interaction of the BioMEMS devices with physiological environments. BioMEMS developed for drug delivery applications include microneedles, microreservoirs, and micropumps to achieve targeted drug delivery. The biocompatibility of BioMEMS is further enhanced through the application of tissue and smart surface engineering. This involves the application of nanotechnology, which includes the modification of surfaces with polymers or the self-assembly of monolayers of molecules. Thereby, the adverse effects of biofouling can be reduced and the performance of devices can be improved in in vivo and in vitro conditions. © 2013 Wiley Periodicals, Inc

Comparison of Antibacterial Effect of Fluoride and Chlorhexidine on Two Cariogenic Bacteria: An in Vitro Study

Statement of problem: Dental plaque is the main source for dental caries and there is no proper vaccine that can affect dental plaques. Objectives: Daily use of an efficient anti-plaque product can be very beneficial in plaque control and, thus, prevention of caries. This study aims to evaluate the antibacterial effects of four products of Chlorhexidine and Fluoride on two types of cariogenic bacteria. Materials and Methods: In this in vitro study, the antibacterial effect of Chlorhexidine and Fluoride (gel and solution) against Streptococci Sanguis and Sobrinus was evaluated. Chlorhexidine gluconate 1% gel (Corosodyl, France), Chlorhexidine gluconate 2% solution (Consepsis, Ultradent, US), Sodium fluoride 0.2% solution (Oral-B, US) and Acidulated Phosphate Fluoride 1.23% gel ( Denti-Care, Canada) were used. The disc diffusion method was used for testing bacterial sensitivity. The data were analyzed using paired t-test and Chi-square test. Results: In comparison with the negative control, each of the four gels and solutions showed antibacterial effects but the effects were not statistically significant for fluoride solution (P=0.217). For S. Sobrinus, the mean diameter of inhibition zone around the discs coated with fluoride gel (F g), fluoride solution (F s), Chlorhexidine gel (CHX g) and Chlorhexidine solution (CHX s) were 19, 9, 21.5 and 27.5mm, respectively. For S. Sanguis, the mean diameter of inhibition zone around the discs coated with F g, F s, CHX g and CHX s were 17, 11, 17 and 25mm, respectively. CHX s had the most effect on both bacteria and F s had the least. CHX g and F g were less effective than CHX s, respectively. Conclusion: The results demonstrated that 2% CHX s and 1.23% F g can be effective on inhibition of the growth of some of cariogenic bacteria. Therefore, these agents can be used in the prevention of Early Childhood Caries