369 research outputs found
Precision Health and AI: improving health for everyone - Arjun Panesar (DDM Health)
No full textThis video is the twelfth talk from our two day Future Blood Testing: Challenges & Opportunities Event that took place on the 14/09/2022.
Precision Health and AI: improving health for everyone - Arjun Panesar (DDM Health)
Bio: Arjun Panesar is the founder of DDM Health, providers of clinically-validated digital health solutions to over 1.8 million people. Benefiting from almost two decades of experience in big data, AI and AI ethics, Arjun leads the development of evidence-based digital innovations that harness the power of machine learning to provide precision medicine to patients, health services, and governments. Arjun’s work has received international recognition featuring in the Forbes, New Scientist, BBC and The Times. Arjun is a best-selling author on the topics of healthcare and AI, authoring two editions of Machine Learning and AI in Healthcare, and contributing to Handbook of Global Health, a major reference work. Arjun is an advisor to the Information School, University of Sheffield, Fellow to the NHS Innovation Accelerator, visiting lecturer at University of Warwick Medical School, and was recognised by Imperial College as an Alumni Leader for his contribution and impact to society.
Further details on this event can be found at: https://futurebloodtesting.org/event/13-14-09-2022/
This video is an output from the Future Blood Testing Network which is funded by EPSRC under Grant Number EP/W000652/1
YouTube Link: https://youtu.be/clPmdeLP5_
Financial Management of Globalization of Developing Countries
No full texthuman development, economic growth, globalization, inequality, poverty
Freedom of choice or force of circumstance? : Eastern European sex-workers in the Republic of Cyprus ; paper for the conference 'Alltag der Globalisierung. Perspektiven einer transnationalen Anthropologie', January 16-18, 2003, Institute of Cultural Anthropology and European Ethnology, Johann Wolfgang Goethe University, Frankfurt am Main
No full textThis paper focuses on Eastern European migrants who, since the beginning of the 1990s, are entering the Republic Cyprus as “artistes”. This is a visa permit status as well as an euphemism for short-term work permits in the local sex industry. In addition to exploring the migrational experiences of these women and their living and working conditions in the Republic of Cyprus, the paper reconstructs, empirically and analyt ically, the connection between immigration and the local sex industry. Here, several categories of social actors and institutions in Cyprus are actively involved. The rhetoric of government representatives, entrepreneurs and clients in the sex business on the one hand is contrasted with the discourse of local NGO representatives concerned with immigrants’ rights on the other hand. The paper comes to the conclusion that all of these discursive positions ultimately do not do justice to the complex process of decisionmaking that women undergo who migrate into the sex industry. Either, freedom of choice is emphasized – such as by entrepreneurs and the government – or the domination of women – as in the public statements of the NGO. In order to analyze the ambivalent tension between freedom of choice and submission to force by which the women’s decision is characterized, the author employs Michel Foucault’s concept of governmentality, which describes forms of political regulation that use the individual’s freedom of action as an instrument to exercise power
Fine-tuning generative models
No full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 73-76).Deep generative models have emerged as a powerful modeling paradigm for making sense of large amounts of unlabeled real-world data. In particular, the representations produced by these models have proven to be useful both in improving human understanding of the factors of variation in the original dataset and in downstream tasks such as classification. Most current algorithms, however, require training a bespoke model from scratch, which can be both expensive and time-consuming. Instead, we propose various methods of fine-tuning pre-trained generative models to achieve these goals, and evaluate these methods quantitatively on few-shot classification and interpretability tasks.by Arjun Khandelwal.M. Eng.M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc
Improving parking garage efficiency using reservation optimization techniques
No full textParking in urban and suburban districts is becoming increasingly problematic due the information gap between the parking garages and the average commuter. This thesis describes and evaluates techniques that can be implemented by parking garages to augment parking garage efficiency. The issues studied in this thesis were i) Real-time tracking of car position ii) maximizing the number of reservations made for the parking garage by re-arrangement of existing reservations (Reservation Defragmentation) and iii) maximizing revenue for the parking garage through increased occupancy (Revenue Management). For the tracking problem, in order to be able to track the real-time position of the vehicle inside the parking garage, we have proposed two techniques. The first one involves a high accuracy algorithm that takes as input a higher number of sensor values (high accuracy) and the second one is a lower cost algorithm that takes as input fewer number of sensor values (low cost). We simulated various conditions of sensor failure rate and determined our metric to be number of tracked points as a percentage of the path to the destination. We determined limitations of these algorithms with respect to maximum speed of cars and inter-car distance. For the reservation defragmentation problem, we looked at increasing occupancy efficiency for i) Next day reservations and ii) Current day reservations. For this problem, we implemented three algorithms. For next day reservations, we established metrics to determine the efficiency of the algorithm including number of free parking spots created and reduction in lengths of free space in between the reservations. For current day reservations, our metric was the increase in maximum occupancy observed due to defragmentation. For increased revenue management, we suggested the application of two techniques: Booking limits and Overbooking. In booking limits, two-fare class of parking was suggested and the number of spots that need to be reserved for higher class (Capacity of garage - booking limit) was determined for probability distributions of customer arrival such as Poisson distribution. Since the practice of overbooking is done in order to compensate for the no-shows that occur despite reservations made, we have suggested an algorithm to determine the amount of overbooking based on a Gaussian distribution of customer ‘no-shows’. We obtained the following results for the algorithms implemented. In case of the tracking algorithm, as the sensor failure rate increased, the inaccuracy of the two proposed algorithms also increased. For 2% failure rate, we track 0.4% of the incoming cars inaccurately (given that a tracking is marked as correct if 75% or less of all sensors along the path of the car fail). In case of reservation defragmentation, we obtained best results for Recursive First-Fit algorithm. For next day reservation defragmentation, using a mean of 15% cancellation of reservations resulted in 14.6% decrease in occupied parking spots which can then lead to increased occupancy and 46.3% decrease in inter-reservation free space sizes for a 1000 arrival reservation system. The reservations were exponentially distributed with a mean of 20 reservations/hour. For current day reservations, we were able to increase maximum occupancy of the parking garage by 5.5% using Recursive First Fit algorithm. Among other conditions, we have evaluated Poisson arrival distribution with corporate arrival rate 100 cars/hour (Flintsch et al., 2006) [56] and corporate fare twice of leisure fare. For this condition, protection level (number of parking slots reserved for corporate class) is determined to be 20% of garage capacity. We also evaluated Binomial distribution with probability of incoming customer to be corporate customer as 0.5 and corporate fare twice of leisure fare. For this condition, protection level is determined to be 50% of garage capacity. We evaluated overbooking for several combinations of No-show rates, mean and standard deviation values and the highest amount of overbooking we obtained was 1.93 times maximum garage capacity and this implies that permitting this number of reservations for the parking garage would minimize the number of parking spots being under-utilized and increase the revenue of the parking garage operator due to effective use of parking spots. The algorithms have been simulated for different arrival distributions (for Revenue Management), different arrival rates (tracking) as well as variable durations of stay (reservation defragmentation). Besides the problems mentioned, there are certain other aspects, such as generalizing the tracking algorithms for parking garages of arbitrary layouts represents the work that needs to be done in the future.M.S.Includes bibliographical referencesby Arjun Ra
Evaluate the Transfer Length and End Region Cracking of Prestressed Girders using 300ksi Strands
No full textThe primary goal of the project is to introduce 300ksi strands to TxDOT bridge design standards for I-girder design. The benefits of transitioning to 300ksi strands include material and labor cost savings, and increased design flexibility. Additionally, increased strength can allow for shallower girder depths while achieving equivalent or greater span lengths compared to girders utilizing 270ksi strands.TxDOT-0-7154Civil Engineerin
Data Quality Management Tool for Service Management Platform
No full textData is a crucial element in every information system and software application. Data quality concerns are not limited to Information Technology (IT) but involve various science realms. The growth of data is not a new phenomenon, “big data,” “data asset,” “data-driven business,” “data warehouses,” and “data lakes” are accepted as common terminologies. The value from data can only be harnessed if it meets specific standards and has the required characteristics. The investment in artificial intelligence, machine learning, and automation will go in vain if there are no data quality checks in place. Data quality management has long been studied in various fields. The studies have produced several frameworks and methodologies to work with data quality management. However, the service management domain of service science discipline, particularly IT Service Management (ITSM), has been challenged by data quality issues in recent years.
The ITSM implementation is facilitated and driven by platforms, such as ServiceNow. The capabilities of ServiceNow expand beyond the conventional ITSM platform. It aims to address IT concerns and service management of enterprises.
The thesis discusses and elaborates on data quality problems found in ServiceNow, an enterprise service management platform. It touches on available and applied solutions, then presents a pragmatic solution developed to address any data quality issues. It provides extensive details on the design and development of the tool, which forms a central part of the solution. Finally, concrete evaluations are presented using practical and real-world cases
iii TABLE OF CONTENTS
No full textI would like to thank Dr. Philip Kenkel, my thesis advisor for accepting me as a graduate research assistant during my hard times and allowing me to work on this project. Sincere thanks go to him for his guidance, encouragement and the valuable time that he has provided to me during the preparation of this thesis. I would also like to thank my committee members Dr. Damona Doye and Dr. Rodney Holcomb for their continuous support and advice during the thesis work. I would also like to remember my parents and thank them for their continuous support and for the burden they took to raise my academic career. I would also like to thank my sisters for their love and encouragement. I cannot forget my grandfather at this moment, without whom, I would not have reached at this position. Thanks also go to my girlfriend who continuously supported, encouraged and guided me whenever needed. I would also like to thank all the Nepalese friends and families in Stillwater, Oklahoma who made my stay in Stillwater as home away from home. I would also like to thank all my friends in the Department of Agricultural Economics from whom I have learned a lot and thanks to them for creating a friendly atmosphere
Understanding the causes of decline in the health of Rupa Lake, Nepal
No full textMeeting: Celebrating Dialogue : An International SAS2 Forum, November 3,
2008, Carleton University, Ottawa, ON, CASAS reports are made available in order to provide timely access to the information by interested researchers. This report has been subject to an internal review process to ensure accuracy and quality.This report provides information on the Social Analysis System (SAS) through which local groups were enabled to analyze the degradation and decline of their lake ecosystem. Effects can be traced to government policies that shifted ownership and control of forests from local communities to government agencies. Slash-and-burn agriculture on national forest land became common; flooding and numerous landslides were provoked by land clearing. The surface area of the lake has declined by almost 50%. All stakeholders made a commitment to strengthen and revitalize people-centered efforts, so that actions would have more local ownership and continuity
Raw data for "Activation of oligonucleotide polyanions using collisions, electrons and photons in a timsOmni platform"
No full textRaw mass spectral data used to prepare the figures of the article "Activation of oligonucleotide polyanions using collisions, electrons and photons in a timsOmni platform", by Frédéric Rosu,1 Rim Chiba,1 Arjun Mani Mallika,1 Athanasios Smyrnakis,2 Jean-François Greisch,3 Dimitris Papanastasiou,2 Valérie Gabelica1*
1 School of Pharmaceutical Sciences, University of Geneva, 1205 Geneva, Switzerland.
2 Fasmatech Science & Technology, 15232 Chalandri, Athens, Greece.
3 Bruker Switzerland AG, 8117 Fällanden, Switzerland.
* Corresponding author: [email protected]
The data is organized by Table or Figure number as in the manuscript main text and supporting information
- …
