5,295 research outputs found
Sen-Lab-LMS/Senescence_nuclear_features: Publication_version_2.0
No full text<p>Author checklist.</p>
The Contributions of Professor Amartya Sen in the Field of Human Rights
No full textThis paper analyses the work of the Nobel Prize winning economist Professor Amartya Sen from the perspective of human rights. It assesses the ways in which Sen's research agenda has deepened and expanded human rights discourse in the disciplines of ethics and economics, and examines how his work has promoted cross-fertilisation and integration on this subject across traditional disciplinary divides. The paper suggests that Sen's development of a 'scholarly bridge' between human rights and economics is an important and innovative contribution that has methodological as well as substantive importance and that provides a prototype and stimuli for future research. It also establishes that the idea of fundamental freedoms and human rights is itself an important gateway into understanding the nature, scope and significance of Sen's research. The paper concludes with a brief assessment of the challenges to be addressed in taking Sen's contributions in the field of human rights forward.Amartya Sen, human rights, poverty, freedom, obligation, capability approach, meta-rights, entitlements, opportunity freedom, liberty-rights
Inequalities, Agency, and Well-being: Conceptual Linkages and Measurement Challenges in Development
No full textdevelopment, inequality, gender, well-being, agency, capability, distribution, Sen
Proactive information retrieval
No full textUsers interact with digital systems with some task in his mind. An example of a task could be writing a research paper on a topic. Tasks can be single or multi-staged. In the process of accomplishing their task objectives, a user often needs to interact with an information retrieval (IR) system to address one or more information needs which arise while working on their task, e.g. for writing their research paper on a chosen topic, the user needs to look for existing research works related to the topic. Traditional IR systems do not take into account a user's task intent while showing search results to the user for a specific query submitted by the user. In our work we propose next generation IR systems (i.e. proactive IR systems) which seek to anticipate the user's underlying task from his interaction with a digital system to automatically identify their information needs and to suggest potentially relevant information sources to help the user to accomplish his task
OVERCOMING POSITIVISM IN ECONOMICS: AMARTYA SEN'S PROJECT OF INFUSING ETHICS INTO ECONOMICS
No full textLogical Positivism, which arose in philosophy early in the twentieth century, proclaimed the sharp distinction between facts and values. Despite objections at the time, positivism was imported into economics in the 1930s. Over time, objections lessened; economics was transformed and ethical considerations were driven out of its core. In the 1950s, debates about positivism arose within the discipline which had exported it. According to the American philosopher Hilary Putnam, the fact/value distinction is now discredited in philosophy. If that is so, the methodological foundations of contemporary economics are also discredited. In this article I examine Amartya Sen’s moral science of economics. First, I will present his historical account of the connections between economics and ethics. Sen claims that there was a close connection between the two until positivism was imported. Second, I will sketch some of Sen’s ethical objections to modern economics, which is still suffering from positivism. Finally, I will lay out some of his ideas on how economics can be returned to an ethical path. Once the ground has been cleared of positivism, ethics can re-emerge in economics in various ways. One path has been marked out by Sen.Teaching/Communication/Extension/Profession,
MADS: A Multi-modal Academic Document Segmentation Dataset for Smart Question Bank Management
No full textIn today’s world, most major academic institutes and organizations conduct competitive exams to assess eligibility of students for admission or recruitment. Due to the rising craze among participants, traditional methods are not optimized enough to get ahead in the race. The inclusion of AI enabled tutoring is mandatory for such exams. One such area of implementation is smart question bank management system. Though we have large volumes of questions of competitive exams in physical mode, however, they are harder to process visually for systems as they consist of several types of text and non-text elements such as numbers, equations, images alongside textual paragraphs. For this purpose, we propose MADS, which is a multi-modal academic document segmentation dataset consisting of images of documents containing heterogeneous questions from the competitive exams like GMAT, GRE, GATE, SAT, UGC-NET. These documents consist of textual paragraphs along with numbers, images and equations. The dataset comes with bounding box annotation in two popular format YOLO and PASCAL-VOC formats to aid the development of efficient document segmentation algorithms. Additionally, benchmarks have been provided for state of the art deep learning based implementations such as Faster RCNN and YOLO-v8. From application point of view, the proposed dataset can identify different objects in an image so that later it can be used for semantic relationship and question answering applications enhancing comprehension and personalized learning experiences, thus, supporting the goal of providing quality education
Unraveling the Influence of Training Data and Internal Structures in Large Language Models for Enhanced Explainability (Student Abstract)
No full textRecent advances in deep learning have expanded the application of large language models (LLMs) across fields such as medicine, finance, and education. Understanding the mechanisms underlying these models is essential to mitigate issues like hallucinations and bias. This study provides deep learning practitioners with insights into how specific training data points and internal structures influence model behaviour. Using influence functions and mechanistic interpretability, we will analyze the impact of data on model predictions across various tasks. Preliminary findings indicate that semantic search techniques, such as FAISS, enable efficient identification of influential training points in GPT-2 small. Future work will extend these methods to additional tasks and more complex models, with a focus on further elucidating LLM structures to improve interpretability
Adventure Tourism and its Future Potential in Ha Tinh, Vietnam
No full textDue to the lack of information about adventure tourism, the client of the thesis, Thanh Sen Travel was not consider adventure tourism as the product of the company. With the belief that Ha Tinh was a potential city to develop adventure tourism, the purpose of the thesis was to investigate the possibility and potential of the city. Therefore, the thesis would provide the company with more information about adventure tourism, identified potential locations and customer segments. The author wanted to persuade the company to add adventure tourism as a new feature to attract new customers coming to the region.
In addition to secondary sources, primary sources were collected via individual qualitative interview of 9 travelers to find a potential target tourist group. Thanh Sen Travel helped the author in discussing the potential adventure tourism activities as well as giving local data to help with the completion of the thesis
Spectral characteristics for a spherically confined- a/r+ br2 potential
No full textSource type: Electronic(1
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