Spatial Wireless Channel Prediction under Location Uncertainty

Spatial wireless channel prediction is important for future wireless networks, and in particular for proactive resource allocation at different layers of the protocol stack. Various sources of uncertainty must be accounted for during modeling and to provide robust predictions. We investigate two channel prediction frameworks, classical Gaussian processes (cGP) and uncertain Gaussian processes (uGP), and analyze the impact of location uncertainty during learning/training and prediction/testing, for scenarios where measurements uncertainty are dominated by large-scale fading. We observe that cGP generally fails both in terms of learning the channel parameters and in predicting the channel in the presence of location uncertainties.\textcolor{blue}{{} }In contrast, uGP explicitly considers the location uncertainty. Using simulated data, we show that uGP is able to learn and predict the wireless channel

VOCAB4ME: A TOOL THAT PROVIDES VOCABULARY RECOMMENDATIONS FOR PUBLISHING LINKED DATA

The web before linked data was a database of html documents. These documents were meant for human consumption and it was hard for machines to make sense of data in html documents. The linked data was introduced with the aim of making the web a global database of data that is machine processable. Linked Data describes a method of publishing structured data so that it can be interlinked and become more useful. Realizing the promise of linked data a lot of people started publishing linked data. But the process of publishing the huge amount of existing data is cumbersome and usually takes someone very knowledgeable to do it. Publishing linked data on the web requires finding appropriate vocabularies that describe the semantics of the data. Finding such vocabularies is difficult to a new user. The proposed system will suggest vocabularies to use when somebody is trying to publish linked data. The system does so by using string similarity metrics to match entity and property names in our dataset to Class and Property names in existing RDF vocabularies

CIP2A is a critical DNA damage response protein that drives basal-like breast cancer

Basal-like breast cancer (BLBC) is an aggressive and therapeutically most challenging breast cancer subtype, due to a lack of druggable breast specific surface receptors (ER, PR, HER2) or driver mechanisms. BLBC patients are treated mainly with standard chemotherapies but due to poor patient stratification strategies, a vast majority of patients receive aggressive chemotherapy even though some of them could be spared from its unnecessary side effects. Protein Phosphatase 2A (PP2A) is an important serine-threonine tumor suppressor phosphatase and its inactivation is an important requirement for malignant transformation in humans. In this dissertation, we demonstrate the role of PP2A inhibitor protein CIP2A (Cancerous Inhibitor of PP2A) in BLBC. We identified a novel PP2A-independent role for CIP2A as a non-genetic driver protein and a biomarker of poor prognosis in BLBC. We discovered that CIP2A interacts with DNA damage response protein TopBP1, prevents its recruitment at the site of DNA damage and allows the progression of damaged cells into mitosis. We further established that CIP2A drives BLBC by coordinating the BLBC hallmarks. CIP2A controls the high proliferation activity of MYC and E2F1 by preventing their dephosphorylation by PP2A but also promotes high genomic instability by deregulating the G2/M checkpoint (PP2A-independent role). We also identified that CIP2A is a synthetic lethal target in BRCA mutant BLBCs and established that CIP2A is selectively more important in predicting prognosis of basal-like TNBC patients compared to non basal-like TNBC subtype. To develop these findings towards clinical utility, we further developed a robust CIP2A transcriptional signature and highlighted several applications of this tool for BLBC patients. The CIP2A signature can predict the aggressivity of breast cancer and it was used to identify drugs and drug combinations that show clinical benefit for the different stratified BLBC subgroups. Collectively, this dissertation reports the yet uncharacterized role of CIP2A in DNA Damage response (DDR), BLBC tumorigenesis, and its potential use as a personalized medicine strategy for effective clinical management of BLBC. CIP2A on kriittinen DNA-vauriovaste proteiini, joka toimii basaalisen rintasyövän ajurina Basaalinen rintasyöpä (BLBC) on hoidollisesti kaikkein haastavin rintasyövän alatyyppi sillä yleensä sitä ei voida hoitaa täsmälääkkeillä. Tämä johtuu solun pintareseptorien tai targetoitavien ajurimekanismien puutteesta. BLBC-potilaita hoidetaan pääasiassa tavanomaisella kemoterapialla mutta koska keinoja potilaskohtaiseen hoidonvalintaan ei ole olemassa, hyvin suuri osa potilaista saa aggressiivista kemoterapiaa, vaikka osa heistä voitaisiin säästää sen sivuvaikutuksilta. Proteiinifosfataasi 2A (PP2A) on tärkeä seriini-treoniini kasvunestäjäfosfataasi ja sen inaktivaatio on edellytys syövän synnylle ihmisellä. Tässä väitöskirjassa olen tutkinut PP2A:ta inhiboivan CIP2A-proteiinin (Cancerous Inhibitor of PP2A) roolia BLBC-syövissä. Väitöskirjatutkimuksessa osoitin CIP2A:n toimivan sekä ei-geneettisenä ajuriproteiinina että biomarkkerina huonoennusteisessa BLBC:ssä. Erityisen tärkeä oli havainto, että CIP2A on selektiivisesti tärkeämpi määrittämään basaalisen kaltaisten kolmoisnegatiivisten (TNBC) potilaiden ennustetta. Mekanistisesti löysimme CIP2A:n vuorovaikutuksen DNA-vauriovasteproteiini TopBP1:n kanssa. Tämä mekanismi estää TopBP1:sen ohjautumisen DNA:n vauriokohtaan edistäen vaurioituneiden solujen siirtymistä mitoosivaiheeseen. Havaitsimme myös, että CIP2A kykenee koordinoimaan useita BLBC:lle tunnusomaisia mekanismeja. CIP2A kontrolloi onkogeenisten MYC- ja E2F1-transkriptiotekijöiden aktiivisuutta estämällä niiden PP2A-välitteisen defosforylaation, mutta myös edistää genomista instabiliteettia estämällä solusyklin G2/M tarkastuskohtaa (PP2A:sta riippumaton rooli). Havaitsimme myöskin, että CIP2A on synteettisesti letaali terapiakohde BRCA-mutanteissa BLBC:eissä. Työssä kehitin myös CIP2A:n säätelemään geeniekspressioprofiiliin perustuvan signature-työkalun ja osoitin että se ennustaa rintasyövän aggressiivisuutta, ja että sitä voi käyttää niiden lääkkeiden ja lääkeaineyhdistelmien tunnistamiseen, jotka erityisesti toimivat BLBC-alatyypin soluja kohtaan. Yhteenvetona tässä väitöskirjassa kuvataan aiemmin julkaisematon CIP2A:n rooli DNA-vaurion korjausmekanismissa (DDR), BLBC:n tuumorigeneesissä, ja potentiaalinen käyttö yksilöllistetyn lääketieteen strategiassa, joka tähtää BLBC potilaiden entistä tehokkaampaan kliiniseen hoitoon

Fine-grained Energy and Thermal Management using Real-time Power Sensors

With extensive use of battery powered devices such as smartphones, laptops an

Infrastructure-as-Code: Automating the Deployment on AWS using Terraform

In my master’s project, I used Terraform to create a scalable infrastructure on Amazon Web Services (AWS) for my personal website. Terraform is an open-source infrastructure-as-code (IAC) tool that allows you to create, manage and provision infrastructure resources, such as virtual machines, storage accounts, networks, and more, across multiple cloud providers and on-premises data centers using a declarative configuration language. A scalable infrastructure is important because it enables a system or application to handle increasing amounts of traffic or workload without experiencing performance issues or downtime. It ensures that the system remains responsive, available, and reliable as an organization grows or its user base expands. Amazon Web Services (AWS) is a comprehensive cloud computing platform offered by Amazon. It provides a broad range of cloud-based services, including compute, storage, networking, database, analytics, machine learning, security and more. These services are designed to help organizations of all size to build, deploy and scale applications and infrastructure in the cloud with ease and flexibility. This project highlights the benefits of Infrastructure as Code and the power of Terraform with AWS for automating infrastructure deployment

Management System for a Restaurant

The Management System for a Restaurant is a web application that allows customers to make online orders by choosing their favorite food items from the restaurant\u27s menu. This website\u27s user-friendly layout organizes a variety of food items. Customers can order food courses and items online and pick them up at a nearby location. This web application consists of a database that stores information about customers, the food menu, and inventory. This application provides a feasible way to order inventory for owners. The motive for designing this web application is to encourage the cloud kitchen concept. Nowadays, due to COVID, most customers are attracted to ordering food online, which is more convenient. Due to this transition, it’s imperative that restaurants provide online services to recover from their past financial crises. Customers and restaurants benefit equally from it. This application has the scope of enhancing the existing application in terms of performance, efficiency, and an effective user interface by using the Model-View-Controller (MVC) framework and bootstrap technologies

A Mixing Engineer’s Portfolio

The project is a cooperation of engineering and mixing skills with the talents of student artists on Berklee Valencia campus. Collaborations with student musicians of various genres and musical backgrounds is the main course of the project. The goal is to enhance mixing skillsets to be able to deliver world-class sounding music of various styles and genres in terms of the soul of the music and the sound of it. The approach for mixing music is totally dependent on the creative and technical aspects of the music, the purpose and also the market it is focused to cater to. To be able to capture the essence of the artist’s creative vision with the state-of-the-art methods and technology has been the main focus of the project. Innovative techniques, based on the old tried-and-tested methods to record and mix have been explored for future prospects. A variety of mixes of varied genres have been accomplished throughout the course of the project.https://remix.berklee.edu/graduate-studies-production-technology/1134/thumbnail.jp