593 research outputs found
The Responsibility to Protect: Norms, Laws and the Use of Force in International Politics
No full textThis volume is a collection of the key writings of Professor Ramesh Thakur on norms and laws regulating the international use of force. The adoption of the Responsibility to Protect (R2P) principle by world leaders assembled at the UN summit in 2005 is widely acknowledged to represent one of the great normative advances in international politics since 1945. The author has been involved in this shift from the dominant norm of non-intervention to R2P as an actor, public intellectual and academic and has been a key thinker in this process. These essays represent the author's writings on R2P, including reference to test cases as they arose, such as with Cyclone Nargis in Myanmar in 2008. Comprising essays by a key thinker and agent in the Responsibility to Protect debates, this book will be of much interest to students of international politics, human rights, international law, war and conflict studies, international security and IR in general
The Life Model of Nisargadatta Maharaj as Interpreted by Ramesh Balsekar
No full textRamesh Balsekar (1917–2009) was a disciple of Nisargadatta Maharaj (1897–1981). Nisargadatta Maharaj lived in Bombay and taught what he realized: For doing our dharma everything is provided for us. Thus we can focus our attention on discovering “Who one is“ and let life flow. In 1996 the author of this article had a short conversation with Ramesh Balsekar, who presented his way of understanding the teaching of Nisargadatta Maharaj
A novel design for an RF MEMS resistive switch on PCB substrate
No full textCopyright @ 2008 Stimulation Action on MEM
AI-Powered Investment Decision Support Systems: Building Smart Data Products with Embedded Governance Controls
No full textThis paper explores some of the possible investment decision support systems powered by artificial intelligence, what components they include and how they operate. Progressing further, we analyze how different artificial intelligence and machine learning bases algorithm types, using different initial data and solving different tasks from simple classification of predefined assets to high-level algorithmic decision generation and implementing task can be combined together and layered to obtain a hierarchical multi-module architecture of the investment decision support system, which would maximize the advantages and minimize the disadvantages of utilizing artificial intelligence methods in the context of generating synthetic market predictions by the investment decision support system. Another critical aspect of investment decision support systems is the aggregation and optimization of the raw signals received from the prediction modules into trading signals, actionable within the high-frequency trading framework and deployable by algorithmic trading systems. We muse upon the possible trading signals aggregation function types and optimization traffic routing from the aggregated trading signals up to the algorithmic trading systems.
Within the next decade or so, investment decision support systems, generating synthetic market predictions and supporting traders dealing with tradeable assets, financial markets and instruments, will be heavily augmented and empowered with Artificial Intelligence and Machine Learning innovative algorithms and techniques, much the same way as classical industrial production architectures operated and supervised within the boundaries of the predetermined parameters are augmented and supported by Industrial AI and Machine Learning algorithms nowadays. Some of the main stages of decision making on the part of such systems follow the stages of cognitive vision and cognitive speech to some extent, observing the abstraction level ontology from raw primary inputs, such as images, sounds and other sensory data information for cognitive vision and cognitive speech systems to more complicated systems patterns formed on the system cognitive level
On the derived functors of the third symmetric-power functor
No full textWe compute the derived functors of the third symmetric-power functor and their cross-effects for certain values. These calculations match predictions by the first named author and largely prove them in general
Importance of marriage for Asian Indian women in the U.S.: an exploratory study
No full textThroughout the past century and across various cultures, the concept of marriage has significantly changed from being a union between two families to a union between two individuals. The change has penetrated South Asia, despite collectivism being the norm in Asian Indian culture. The current exploratory study was done to investigate an unexamined area of research namely, the pressure experienced by unmarried Asian Indian women in the United States. A qualitative research design combining ethnographic and grounded theory was used. Ten interviews were conducted with heterosexual, Asian Indian, Hindu women, above the age of 25, and raised in the United States. Four main research questions were addressed: (1) What pressures do family and community put on Asian Indian women to get married (2) What effect does remaining unmarried have on Asian Indian women (3) How do certain factors (i.e., past relationships, religion, skin color, and education) affect how desirable these women are to others, and how desirable they feel? and (4) What are Asian Indian women’s perspectives on marriage? The interview data collected were analyzed to uncover qualitative themes. These themes included the following: the women interviewed felt that all Asian Indian women were born to be brides, that Asian Indian women did not go through a process of separation-individuation as defined in Western psychology, that parents experienced a great deal of shame if their daughters remained unmarried, that a great amount of interpersonal conflict with family and friends resulted from staying single, and that most women had felt that they needed to get married before the age of thirty. Although several of the women interviewed stated that they were ambivalent about the idea of marrying someone of Indian origin, the women felt that several factors affected how desirable they were to other members of the Indian community. The findings of this study suggest important implications for clinical psychology training for mental health clinicians. The study suggests that therapists should have an increased understanding of the difference in separation-individuation between Western and Asian Indian culture, the importance of an Asian Indian woman’s external presentation, and the extreme shame that these women may experience by remaining single.Psy. D.Includes bibliographical referencesby Snigdha Ramesh Ratho
Building Trustworthy Agentic Ai Systems FOR Personalized Banking Experiences
No full textArtificial Intelligence (AI) systems have become ubiquitous in contemporary society and have the potential for transformative impact on user behavior. These systems are capable of learning autonomously to personalize their behavior to deliver improved user experiences. However, there exists the potential for unintended consequences, as the same agentic features associated with positive outcomes may also increase the capacity for negative outcomes. Financial services is an example of a domain where deploying AI systems with agentic features would be high risk. The automated decision-making capabilities of these systems could influence billions of dollars. Nonetheless, they would be entrusted with taking actions that affect users without human oversight, such as reallocating entire portfolios of assets in ways that users do not wish. Therefore, a foundational requirement for adopting these systems must be the capacity to build shared norms of beneficial behavior prior to their deployment.
Several commercially available AI systems with agentic features are already deployed in the domain of personal banking. Automated personal financial management combines categorization of transactions followed by predictions of future expenditure and savings to improve budgeting decisions, amongst other impacts. Digital banking assistants embed intelligent conversational agents used primarily for accessing banking information and services. These systems typically operate in conjunction with non-intelligent user interfaces, and thus the extent of agentic features in user-bank interactions is limited. However, envisionable advancements include wider adoption of natural language processing capabilities, comparative financial analysis, and customized query suggestions.
Agentic AI systems must operate under a formal specification of trustworthiness constraints. Therefore, AI agents must embody the technical requirements for trustworthy AI systems. Management of risks associated with agentic AI is a dangerous task given the scale of money flows in financial markets and the unprecedented scale, scope, and speed of analysis, prediction, and execution in such markets. At the same time, AI systems that endow agents with entity-level legal ownership and agency create a scarcity that could be captured in trust funds in the form of wealth to protect a material asset class from better prediction by other agents (all other predictions being sub-optimal). Glücksspiel unter Vertrauensbildung para-poker could be a conceptually rigorous game of chance. Thereby, the proposed system could help to promote beneficial forms of AI agency while governing risks effectively
Automated detection of ultrastructural features at neuronal synapses
No full textSynaptic vesicles are the ultracellular structures responsible for carrying chemical messengers known as neurotransmitters from inside the axon of a neuron to the synaptic junction outside. The variation in size and location of these structures is important in the study of their use and reuse in neurons. We propose a method to locate and estimate the diameter of vesicles in electron microscope images of synapses. We train a U-Net inspired model to perform pixel-wise segmentation of the vesicles against background pixels. We then use contour detection on the resulting segmentation maps to determine individual vesicle centers and effective diameters. To our knowledge, there are no baselines in this task so we establish one on an in-house dataset. Our results show that the proposed model performed well on this task.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2022-05-01The student, Ashwin Ramesh, accepted the attached license on 2020-05-12 at 19:48.The student, Ashwin Ramesh, submitted this Thesis for approval on 2020-05-12 at 20:03.This Thesis was approved for publication on 2020-05-13 at 10:06.DSpace SAF Submission Ingestion Package generated from Vireo submission #15370 on 2020-08-25 at 17:31:20Made available in DSpace on 2020-08-26T23:58:49Z (GMT). No. of bitstreams: 2
RAMESH-THESIS-2020.pdf: 13114758 bytes, checksum: 151b69806aae993f256f0ac16961f07c (MD5)
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Previous issue date: 2020-05-13Embargo set by: Seth Robbins for item 115808
Lift date: 2022-08-26T23:58:55Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemU of I Onl
Designing Scalable Data Product Architectures With Agentic AI And ML: A Cross-Industry Study Of Cloud-Enabled Intelligence In Supply Chain, Insurance, Retail, Manufacturing, And Financial Services
No full textThe emergence of industrial product lines enabled the creation of the most complex products ever. Product models are necessary to design, configure and maintain this complexity. The systems at the core of current scalable product based software development are usually realized as rigid to change data models embodied in relational databases. This makes it expensive to exploit product model data and hampers innovation. Semantic technologies remove many of these problems but until recently lacked the performance and scalability to be put into production for large product lines. With the advent of linked data platforms this has changed. This paper outlines our design considerations for a product model framework based on the linked data principle and motivated by both business and technical needs. We present our architectural blueprint for product models and show how we apply this to three different domains. These domain models cover conventional data products, devising interaction with humans, and facilitating cooperative distributed creation of data collections. Our chosen level of generalization enables us to expose important ideas factored into our framework. It also sets the stage for open collaboration on the development and extension of product model ontologies.
Currently our data products exist as independent implementations to a varying degree addressing their respective business needs. We plan to join forces with partners to realize a family of linked data products describing different fields of human endeavor. Case studies are the ideal method to get involved in such an endeavor. To that end we invite readers to contribute to our effort. In the remainder of the paper we first outline design rationales in Section 1. Section 2 presents a blueprint for a linked data product family. Domain models, realizing components of the product blueprint, are then described in Section 3. The paper is concluded in Section 4
A Field Ion Microscope Study of Interfaces
No full textTitle: A Field Ion Microscope Study of Interfaces, Author: Ramesh Rajagopal, Location: ThodeThis investigation is concerned with the observation of interfaces between f.c.c. and b.c.c. crystals in the field ion microscope. A high vacuum field ion microscope was designed and constructed to operate under liquid nitrogen cooling and helium gas imaging, with facilities for vapour deposition. Platinum and iridium were deposited on tungsten field ion emitters by shadow vapour deposition. The nature and contrast of deposits obtained under various experimental conditions are examined. The atomic matching observed at interfaces is discussed within the limitations of the existing interfacial contrast theory.ThesisMaster of Engineering (ME
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