180 research outputs found
Exploring machine learning models to predict atmospheric water harvesting with an ion deposition membrane
No full textThis work investigates the performance of a novel membrane-based atmospheric water harvesting (AWH) unit under various operating conditions of ambient temperature, relative humidity (RH), and carrier fluid flow rate. Ion deposition membranes (IDMs) were selected for their ability to enhance water uptake by lowering the water vapor saturation pressure at the gas-membrane interface. This effect, achieved through metal ion implantation into PTFE-based membranes, improves water harvesting rates – especially under low RH conditions – by up to a factor of four compared to untreated membranes. The benchmark design was tested over all possible combinations of four distinct carrier fluid flow rates, three temperatures, and six RH values. The yield with a lab-scale prototype was as high as 354 ml/day of water, with an average of 155 ml/day, corresponding to water harvesting rates of 22.13 kg/m2/day and 9.69 kg/m2/day, respectively. The experimental dataset obtained was used to build three machine learning (ML) regression models to predict the amount of water harvested under specific operating conditions. The ML techniques are: Support Vector Regression, Gradient Boosting Regression, and Multilayer Perceptron. These methods achieved accuracy scores as high as 89 %, proving suitable for implementation in the regulation of AWH plants featuring this technology. The best-performing model (Multilayer Perceptron) was used to predict the water harvesting potential on a typical spring day in Jeddah, Saudi Arabia, a region facing severe water scarcity
Mastering Chat GPT Fundamentals, Applications, and Ethical Considerations
No full text<p>Welcome to the world of artificial intelligence and natural language processing, where innovation and advancement are constant companions. This book is your portal to explore the incredible journey of Chat GPT, a state-of-the-art language model that has been at the forefront of conversational AI. Whether you're an AI enthusiast, a technology professional, or simply someone curious about the future of human-machine interaction, this text promises to be an enlightening adventure. Chat GPT represents a breakthrough in the realm of AI-driven conversations. Developed by OpenAI, this language model has been designed to understand and generate human-like text responses, enabling seamless interactions between people and machines. The technology underpinning Chat GPT has evolved rapidly, and it has found applications in a wide range of fields, from customer service chatbots to content generation, personal assistants, and more. The primary aim of this book is to provide you with a comprehensive view of the advancements and applications of Chat GPT. As you journey through its pages, you will learn about the inception and evolution of this technology, the science and engineering behind it, and the myriad ways it is being used to improve our daily lives. The authors aim to bridge the knowledge gap between experts and the broader audience, offering a balanced blend of technical insights and practical relevance. From its early iterations to the cutting-edge versions, you'll see how Chat GPT has evolved and how it continues to push the boundaries of what's possible in natural language understanding and generation. You will explore how this technology is facilitating human-computer interactions, aiding content creators, and even serving as a tool for enhancing communication and productivity in various industries. Whether you're a researcher, developer, or simply a curious reader, this book will help you grasp the underlying principles of Chat GPT, its real-world applications, and its potential for shaping the future of AI-driven communication. You'll discover not only the achievements but also the challenges faced by this remarkable technology as it continues to progress. As you delve into the world of Chat GPT, we invite you to contemplate the exciting possibilities it presents. The advancements discussed within these pages are not just about improving AI, but about how this technology is enhancing our daily experiences, making information more accessible, and bridging the gap between humans and machines. </p>
Tracing the building of Robert's connections in mathematical problem solving: a sixteen-year study
No full textThis research analyzes how external representations created by a student, Robert, helped him in building mathematical understanding over a sixteen-year period. Robert (also known as Bobby), was an original participant of the Rutgers longitudinal study where students were encouraged to work on problem-solving tasks with minimum intervention (Maher, 2005). The research demonstrates how Robert built robust counting techniques by tracing the evolvement of his problem-solving heuristics, strategies, justifications and external representations. The study also examines how Robert made connections to his earlier problem solving. In addition, the origins of Robert’s ideas related to Pascal’s Triangle and Pascal’s Pyramid are investigated. Fifteen sessions were selected between Robert’s fifth grade (February 26, 1993) and post-graduate interviews (March 27, 2009) yielding more than twenty hours of video data. Powell, Francisco, and Maher (2003) model was used for analysis where by each session was viewed, transcribed and coded for critical events to create a comprehensive narrative. The study reveals that mature combinatorial techniques were a part of Robert’s counting strategies as early as middle school. Robert used binary notation to count two-colored candle arrangements and later to count the number of ways a team could win a World Series; modified exponential formulae to account for combinations for a garage door opener, arrangements for n-colored candles and n-toppings pizzas; discovered the combinations formula, C(n, 2), in his eleventh grade; and connected these solutions to Pascal’s identities. In general, Robert looked for patterns in his solutions; generalized the findings; and identified structural similarities in tasks presented to him as he connected three-position garage door opener to three-colored candles arrangements, pizza with four toppings to towers four high, and directions on Pascal’s Triangle to routes for a taxi on a two-dimensional grid. External representations created by Robert served as communication tools for him and provided insight into his problem solving heuristics and mathematical understanding. The research contributes to the growing body of case studies from Rutgers longitudinal study providing evidence that building of early mathematical ideas is the foundation of more advanced learning (Davis & Maher, 1997).Ph.D.Includes bibliographical referencesIncludes vitaby Anoop Ahluwali
Towards an enhanced understanding of bias in pre-trained neural language models: a survey with special emphasis on affective bias
No full textThe remarkable progress in Natural Language Processing (NLP) brought about by deep learning, particularly with the recent advent of large pre-trained neural language models, is brought into scrutiny as several studies began to discuss and report potential biases in NLP applications. Bias in NLP is found to originate from latent historical biases encoded by humans into textual data which gets perpetuated or even amplified by NLP algorithm. We present a survey to comprehend bias in large pre-trained language models and analyze the stages at which they occur in these models, and various ways in which these biases could be quantified and mitigated. Considering wide applicability of textual affective computing-based downstream tasks in real-world systems such as business, health care, and education, we give a special emphasis on investigating bias in the context of affect (emotion) i.e., Affective Bias, in large pre-trained language models. We present a summary of various bias evaluation corpora that help to aid
Third Revision of the Global Surface Seawater Dimethyl Sulfide Climatology (DMS-Rev3)
No full textThis dataset contains all the input data and the Matlab codes for the Third Revision of the Global Surface Seawater Dimethyl Sulphide Climatology (DMS-Rev3)
Shrivardhan Hulswar, Rafel Simo, Martí Galí, Thomas G. Bell, Arancha Lana, Swaleha Inamdar, Paul R. Halloran, George Manville and Anoop S. Mahajan
*corresponding author: Anoop Sharad Mahajan ([email protected])
Details to run the code can be found in the word file: Code details.doc
Contextual bitext-derived paraphrases in automatic MT evaluation
No full textIn this paper we present a novel method for deriving paraphrases during automatic MT evaluation using only the source and reference texts, which are necessary for
the evaluation, and word and phrase alignment software. Using target language paraphrases produced through word and
phrase alignment a number of alternative reference sentences are constructed automatically for each candidate translation. The method produces lexical and lowlevel
syntactic paraphrases that are relevant to the domain in hand, does not use external knowledge resources, and can be
combined with a variety of automatic MT evaluation system
Third Revision of the Global Surface Seawater Dimethyl Sulfide Climatology (DMS-Rev3)
No full textThis dataset contains all the input data and the Matlab codes for the Third Revision of the Global Surface Seawater Dimethyl Sulphide Climatology (DMS-Rev3)Shrivardhan Hulswar, Rafel Simo, Martí Galí, Thomas G. Bell, Arancha Lana, Swaleha Inamdar, Paul R. Halloran, George Manville and Anoop S. Mahajan*corresponding author: Anoop Sharad Mahajan ([email protected])Details to run the code can be found in the word file: Code details.docxTHIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
Clinical Profile and associations of tuberculosis among health care workers in South India
No full textINTRODUCTION :
Every year 1.8 million people in India develop tuberculosis (TB). India accounts for one-fifth of the global TB incidence and is estimated to have the highest number of active TB cases amongst the countries of the world. Many hospitals in India handle large number of tuberculosis cases. The emergence of multidrug resistant tuberculosis has been reported to have caused outbreaks among health care workers in many hospitals. Various authorities have recommended measures to prevent the nosocomial transmission of tuberculosis.
However scientific data demonstrating the efficacy of these measures is lacking.
Delayed diagnosis of active pulmonary TB among hospitalized patients is common and believed to contribute significantly to nosocomial transmission.
Various studies reported a risk of infection among workers exposed to patients with tuberculosis that was four to six times higher than the risk among unexposed workers. However the risk of tuberculosis among health care workers varies considerably among and within hospitals.
Epidemiological studies are needed to identify the high-risk subgroups among health care workers and to identify potential risk factors for transmission of disease. Such observations would lead to further implementation of cost effective infection control measures and analysis of the efficacy of such measures with respect to developing countries like India. These measures might prevent or retard the nosocomial transmission of tuberculosis to both patients and to health care workers.
AIMS AND OBJECTIVES :
1. To identify the risk factors for acquiring tuberculosis among health care workers at a tertiary level teaching hospital in South India.
2. To determine the incidence of tuberculosis among health care workers.
3. To identify the factors associated with a delay in the diagnosis of tuberculosis among health care workers.
MATERIALS AND METHODS :
RESEARCH PROTOCOL:
DESIGN:
1. Prospective and retrospective descriptive cohort study design for determining the incidence of clinical tuberculosis disease among health care workers and to determine the clinical profile of tuberculosis disease among the target population.
2. Case control study design to determine the specific risk factors for acquiring tuberculosis in the target population. Prospectively (from April 2003- August 2004) and retrospectively (from January 1994- March 2003) collected cases will be used.
DURATION:
From April 2003 to August 2004, a sixteen month period.
LOCATION:
Departments of General Medicine units I, II and III, Staff Students Health Services.
SUBJECTS:
INCLUSION CRITERIA:
Health care workers employed at Christian medical college hospital, Vellore who are diagnosed to have tuberculosis.
EXCLUSION CRITERIA:
i. Patients who were diagnosed to have active tuberculosis or have received treatment for tuberculosis prior to joining the health care facility.
ii. Patients diagnosed to have tuberculosis during the pre employment screening.
iii. Patients who are having a relapse of tuberculosis during the study period and if the index episode is prior to January 1994.
RESULTS :
The results of the study are summarized here. The results will be presented in three sections. The first section depicts data regarding the clinical profile of health care workers who developed tuberculosis. The second section
deals with the associations of a more than median delay in the diagnosis of tuberculosis (case-control study). The third section is a case control study designed to identify the risk factors for developing tuberculosis among the health care workers.
CONCLUSIONS :
Health care workers had a higher incidence of tuberculosis than the general population. The incidence of tuberculosis disease among health care workers was 314 cases per 100,000 person years. The incidence of sputum positive pulmonary tuberculosis was 111.06 per 100,000 person years.
• The main sub type of tuberculosis was sputum positive pulmonary. Among the extra pulmonary cases tuberculous lymphadenitis constituted the majority.
• Among health care workers at our institute the only risk factors that were independently associated with tuberculosis were a body mass index <19 Kg/m2 and employment in medical wards.
• No occupational subgroups were found to have an independently increased risk for acquiring tuberculosis.
• There was a significant delay in diagnosis of cases of tuberculosis. The mean delay was 37.98 days. The delay in the diagnosis of smear positive cases could contribute to nosocomial transmission of tuberculosis
A controlled crossover study to assess the role of dietary eliminations in reducing the severity of atopic dermatitis in children
No full textBackground: In the pathogenesis of atopic dermatitis (AD), immune sensitization to food-derived allergens has a role. However, the evidence of allergen sensitization is not a proof of clinically relevant allergy and it has to be confirmed by food challenges so that unnecessary food restrictions in growing children can be avoided. Aims and Objectives: This study was conducted to assess the clinical severity of AD in children after certain dietary modifications and to correlate absolute eosinophil count (AEC) with dietary modification. Materials and Methods: A total of thirty AD children were enrolled randomly into a trial period of egg and cow's milk exclusion diet or control period of egg and cow's milk inclusion diet of 3 weeks. At the end of 3 weeks, patients resumed their normal diet to minimize any carryover effect for next 3 weeks. In the last 3 weeks, the trial and the control groups were crossed over. Patients were assessed at baseline and at the end of each 3-week period using SCORing AD (SCORAD) index and AEC. The data were analyzed using paired t-test. Results: The mean SCORAD at the end of control and trial period was 18.3 and 14.3, respectively, with a mean difference of 3.4, which is statistically not significant (P = 0.165). The mean AEC at the end of control and trial period was 836.5 and 799.6, respectively, the reduction being statistically not significant. Conclusion: Our study could not confirm the beneficial effects of an allergen avoidance diet in AD. We propose that dietary elimination advices should be given only to patients with a definite history of food-induced exacerbations of the disease
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