825 research outputs found
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Relational Care - with Mary Larkin and Manik Deepak-Gopinath [Podcast]
No full textWhat is 'relational care' and how can it improve the day-to-day experience of carers and those they care for? What are its implications for relationships between staff and service users in care settings? And how does the concept of relational care enable us to re-imagine the role of place and space in the experience of care? These are some of the questions we explore in this episode with Mary Larkin and Manik Deepak-Gopinath who recently completed a research project on the value and practice of relational care with older people.
Mary is Professor of Care, Carers and Caring at The Open University in the UK, where her research has focused on carers and caring and adult social care. She is the co-author, most recently of Family Carers and Caring, published in 2023 by Emerald. Manik is a Lecturer in Ageing, also at The Open University, and is a critical gerontologist with interests in the intersection of ageing, place and wellbeing, and in the intimate and family ties of older adults
My Name Is Deepak
No full textThis chapter looks at the author's responses to being given a nickname by his co-workers: Tupac. They do it in a friendly manner, but the author doesn’t understand the connection with the American rapper. It makes him think about who he is, his identity, and how people see him in his adopted country.</p
Sideffective - system to mine patient reviews: sentiment analysis
No full textSideffective is the system to crawl, rank and analyze patient testimonials about side ffeects from common medications. Since the wealth of any mining model is the Data corpus, the data collection phase involved extensive crawling of massive medical websites comprised of user forums from the internet. Subsequently, the raw files were subjected to certain site-specific parsing routines, yielding outputs conforming to a well-defined data model. Currently, the system holds close to 400,000 user testimonials pertaining to more than 2500 drugs/medicines. Sideffective aims at gathering and aggregating this wealth of information, build useful associations and present interesting observations and numeric validations, all in a user-friendly interface. The important issues that we have tried to tackle are: Extracting side effects without relying on pre-built lists, aggregating distribution of different side effect for a give drug, site-specific search, ranking and determining the negativity of reviews. The system has been jointly built by Deepak Yalamanchi and Sangeetha Rajagopalan under the guidance of Prof. Tomasz Imielinski. This thesis focuses mainly on Sentiment Analysis of patient reviews. While most existing sentiment analysis systems are predicated by POS (parts of speech) tagging or Bayesian sentiment analysis methods, the same cannot be applied to medical reviews as they generally carry a negative flavor in them. We thereby approached the problem by identifying the features in the sentence and calibrating the sentiment on a Negativity Meter based on their relation to sentiment words. A feature, as defined for the purpose of this thesis, can be a medicine, a side effect or a symptom. The sentiment of each feature is determined by the aggregate of all its polarities with respect to each sentiment word, where the polarity is determined by an inverse relation to the distance of the feature from the sentiment word. Each sentence is then evaluated by the cumulative polarity of all the features contained in it. Sentiment of a review is determined by individually determining the sentiment of each sentence and then getting a weighted sum score of all the sentences in the review. The accuracy of a sentiment analysis system is, in principle, how well it agrees with human judgments. Experimental results, involving human reviewers (extracted from site: www.askapatient.com) and correlating them back to the negativity rating of each review yield conclusive results, demonstrating the effectiveness of the technique. We have also implemented a customized Lucene search on the data using a multi-review summarization approach and a ranking scheme based on the feature-list. Ranking priority is given to the review that has the largest feature list size.M.S.Includes bibliographical referencesby Deepak Yalamanch
Multi-modal Image Registration for Deep Brain Stimulation Analysis
No full text<p>Deep Brain stimulation (DBS) surgery is microelectrode-guided surgery for the treatment of patients with movement disorders. DBS on deep brain structures requires effective postoperative procedures for analysis of surgical success. Thus, brain shift analysis is an important stage of DBS surgery where pre-operative and postoperative images are compared to measure the brain shift. Since information gained from two images acquired in the clinical track of events is usually complementary, properly integrating useful data obtained from the separate images is challenging. The integration process to bring the modalities involve spatial alignment, a procedure referred to as registration. Registration is typically followed by a fusion step required for the integrated display of the image data. This paper presents a novel approach that focuses on multimodality data fusion to analyze the pre-operative and postoperative CT and MR images. Our multimodal image registration model considers brain images based on a projection-based reference image. The registration is based on sharing mass in a predetermined direction: axial, sagittal, and coronal. Then, the region of interest is registered through modified mutual information based on the overlap rate and a weight assigned to it. Our approach is a combination of both coarse and fine registration techniques.</p>Harikrishna G. N. Rai, Krishnamurty Sai Deepak and P. Radha Krishna,Multi-modal Image Registration for Deep Brain Stimulation Analysis, J. Innovation Sciences and Sustainable Technologies, 1(2)(2021), 189-204. DOI: https://doie.org/10.0608/JISST.2022729673, E-mails: [email protected], [email protected], [email protected]
Gendering global governance
No full textIn this article I map out the major debates on global governance and the feminist critiques of the mainstream interventions in these debates. I argue that the shift from government to governance is a response to the needs of a gendered global capitalist economy and is shaped by struggles, both discursive and material, against the unfolding consequences of globalization. I suggest feminist interrogations of the concept, processes, practices and mechanisms of governance and the insights that develop from them should be centrally incorporated into critical revisionist and radical discourses of and against the concept of global governance. However, I also examine the challenges that the concept of global governance poses for feminist political practice, which are both of scholarship and of activism as feminists struggle to address the possibilities and politics of alternatives to the current regimes of governance. I conclude by suggesting that feminist political practice needs to focus on the politics of redistribution in the context of global governance
Building Thermal Performance Varies During Extreme Heat within Cities
No full textabstract: This document has been superseded by our peer-reviewed publication:
Building Thermal Performance, Climate Change, and Urban Heat Vulnerability, Matthew Nahlik, Mikhail Chester, Stephanie Pincetl, David Eisenman, Deepak Sivaraman, and Paul English, 2017, ASCE Journal of Infrastructure Systems, 23(3), doi:10.1061/(ASCE)IS.1943-555X.0000349
The publication is available at: http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000349
The leading source of weather-related deaths in the United States is heat, and future projections show that the frequency, duration, and intensity of heat events will increase in the Southwest. Presently, there is a dearth of knowledge about how infrastructure may perform during heat waves or could contribute to social vulnerability. To understand how buildings perform in heat and potentially stress people, indoor air temperature changes when air conditioning is inaccessible are modeled for building archetypes in Los Angeles, California, and Phoenix, Arizona, when air conditioning is inaccessible is estimated. An energy simulation model is used to estimate how quickly indoor air temperature changes when building archetypes are exposed to extreme heat. Building age and geometry (which together determine the building envelope material composition) are found to be the strongest indicators of thermal envelope performance. Older neighborhoods in Los Angeles and Phoenix (often more centrally located in the metropolitan areas) are found to contain the buildings whose interiors warm the fastest, raising particular concern because these regions are also forecast to experience temperature increases. To combat infrastructure vulnerability and provide heat refuge for residents, incentives should be adopted to strategically retrofit buildings where both socially vulnerable populations reside and increasing temperatures are forecast
Building and processing a dataset containing articles related to food adulteration
No full textThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (page 69).In this thesis, I explored the problem of building a dataset containing news articles related to adulteration, and curating this dataset in an automated fashion. In particular, we looked at food-adulterant co-existence detection, query reforumulation, and entity extraction and text deduplication. All proposed algorithms were implemented in Python, and performance was evaluated on multiple datasets. Methods described in this thesis can be generalized to other applications as well.by Deepak Narayanan.M. Eng
Digital front end for base-station RF
No full textThe digital front-end (DFE) is the most critical stage in a wireless base-station. The DFE along with the analog to digital converter (ADC) is responsible for bridging the analog RF and IF processing on one side and the digital baseband processing on the other side. The most important reason for replacing analog with digital signal processing is the ability to softly reconfigure the channels in the base station RF in real time, thus allowing for the implementation of various signal conditioning, compensation and mitigation channel non-linear responses. Once tested, these algorithms can be implemented on a proprietary CMOS vector processor and commercial FPGA hardware platforms. In this thesis, we attempt to minimize the design efforts and lower the cost involved in the usage of analog electronics by using sophisticated digital signal processing (DSP) for restoring and enhancing the quality of the wireless channels. This thesis presents a versatile Digital Front-End architecture, which has been simulated using MATLAB/Simulink. The architecture includes the design of robust Digital Up-Conversion (DUC) blocks in the transmit downlink and Digital Down-Conversion (DDC) blocks present in the receiver uplink paths in a wireless base station RF. Crest factor reduction (CFR) schemes help reduce the Peak to Average Power Ratio (PAPR)of the signal entering the base-station and have been implemented widely for code division multiple access (CDMA) and Long Term Evolution (LTE) systems, this is important because if the signal with the high PAPR is allowed to pass through the power amplifier(PA) it will result in the amplifier operating in its nonlinear region creating non-linear distortions in amplitude and phase, and the only other way to avoid this is to back off the signal to the linear region of the amplifier thus reducing its efficiency. The selection and design of the DUC and DDC filters has been compared and optimized to match to the spectral mask requirements mentioned in the 3GPP standards. Crest factor reduction has also been studied in detail and a computationally efficient algorithm for meeting the desired PAPR in accordance with the 3GPP standards will be presented. By using the CFR algorithm, the PAPR of the LTE signal was reduced from 10.8 dB to 7 dB and from 10.5 dB to 8 dB for a WCDMA signal. Finally, we implement Digital Predistortion (DPD) which is a method by which one first stimulates a non-linear power amplifier (PA) with baseband samples and then observes the result of that stimulus at its output. Without this process we will need to use a power amplifier with a higher input power rating which needs to be backed off to operate in its linear region thus reducing the efficiency of the PA used and increasing its cost. The process involves the use of a digital predistorter which creates an expanding nonlinearity which when used in cascade with the PA nullifies the compressing nonlinear characteristics of the PA thus enabling its use in its linear region up to its saturating point. A Look-Up Table (LUT) type Adaptive Digital Pre-Distortion (ADPD) is presented; here we developed an algorithm where the output signal of the PA is used as a reference signal. This reference signal is then used to update the coefficients of the LUT, so that the non-linear responses of the PA will not the affect the amplified signals. In addition, we investigated methods such as the nonlinear auto-regressive moving average (NARMA) and the memory polynomial models. In the latter, the predistorter parameters are calculated from the output signal obtained from the PA through the adaptive functions obtained using the memory polynomial. From these parameters, the predistorted signal is reconstructed and fed to the input of the PA. By using the DPD algorithm the nonlinear distortions of the PA came down by 60 dB when a WCDMA signal was used and by around 40 dB when LTE signal was used. As the PA is the heart of the base-station RF, we show that the main function of the DFE is to ensure a PA linearized output with a high efficiency.M.S.Includes bibliographical referencesby Deepak Gop
Measurement and analysis of oil-gas diffusion at reservoir conditions: application to huff-n-puff EOR in unconventional reservoirs
No full textDue to the extremely low permeability and high depletion rate, primary recovery from unconventional reservoirs is generally low. Huff-n-Puff has proved to be a successful EOR technique in tight formations, such as the Eagle Ford. However, the underlying transport mechanism remains poorly understood. Recent studies show oil-gas diffusion is a key factor in huff-n-puff EOR. Due to concentration gradients, injected gas molecules diffuse into in-situ oil causing it to swell and consequently to be expelled out of the nanopores into the micro- and macro- fractures.
We have designed an experiment with a high-pressure, high-temperature cell having observation windows for the measurement of oil swelling and diffusivity. The measurements have been done on Wolfcamp A oil (API-32), Meramec oil (API-43) and Eagle Ford oil (API-53) with 3 different gas mixtures of methane – ethane, at a temperature of 175°F to evaluate the impact of injection pressure (above and below Minimum Miscibility Pressure-MMP), injectate gas composition, API gravity and viscosity of oil on oil-gas diffusivity.
The results show that the diffusivity of injectate gas into the oil phase as a function of pressure and increases to maximum at MMP, beyond which it decreases. Enrichment of the injection gas increases the oil-gas diffusivity at the same pressure. Regardless of injection pressure, for the gas mixture C1/C2 (72/28 mole%) the diffusion coefficient varies between 10-11 m2/s to 10-10 m2/s for Wolfcamp A oil; 10-10 m2/s to 10-9 m2/s for Meramec oil and 10-9 m2/s to 10-8 m2/s for Eagle Ford oil.
Tight reservoirs generally have a high matrix tortuosity, which impacts the diffusion efficiency in the porous media. Using tortuosity values available in the literature and diffusivities of oil gas systems measured in this study, we estimate that the injected gas can only travel 0.2-0.9 ft away from the fracture-faces during 6 months of gas injection. Low tortuosity and high diffusion rates favor economic recoveries. This study highlights the importance of stimulated reservoir area (SRA) characterization, nanoporous tortuosity and diffusivity measurements in optimizing huff-n-puff recovery in shales
EXPERIMENTAL STUDY OF EFFECT OF PROPPANT CONCENTRATION, TYPES, SIZES, ROCK MINERALOGY AND OVERBURDEN STRESS ON FRACTURE CONDUCTIVITY
No full textHydrocarbon production from unconventional reservoirs, particularly shales, requires massive hydraulic fractures to expose the large surface areas within the formation and provide a conduit to the wellbore. Proppants are pumped along with the fracturing fluids during hydraulic fracturing to keep the fractures open. For the economic production of hydrocarbon, maintaining the conductivity of such fractures is critical. However, there are different mechanisms such as proppant crushing, fines migration, proppant embedment and proppant diagenesis etc., which can lead to the significant reduction in fracture conductivity with time. The severity of each mechanisms varies substantially depending on the rock mineralogy, proppant type, proppant concentration, proppant size and overburden stress. Field observations reveals the overall performance of well productivity depends on fracture conductivity which is influenced by the combination of these factors. Lab experiments conducted under simulated reservoir conditions can help to systematically evaluate the effect of different parameters on fracture conductivity. This study focuses on the effect of proppant concentration, proppant type, proppant size, rock mineralogy and overburden stress on the propped fracture conductivity under simulated reservoir conditions. Different damage mechanisms including proppant crushing, embedment and diagenesis and their severity to the conductivity reduction have also been evaluated.
Experiments were conducted with shale platens machined from Eagle Ford and Meramec formations. Proppants with different concentration (varying form 1.5 lb/ft2 to 4 lb/ft2), different sizes (20/40, 40/70, 60/100), different types were placed between the two platens and propped fracture conductivity is measured over the period of 7-60 days. Axial stress of 5000 psi was applied to simulate the closure stress which was also varied from 1500 to 7500 psi in different experiments to evaluate the effect of overburden stress on conductivity. The brine composed of 3% NaCl, 0.5% KCl was flowed at a constant rate of 3 ml/min throughout the experiment. In some experiments, 0.05 molar Na2CO3 was added to raise the pH of the brine up to 10.
Testing was done to study the effect of proppant concentration using 60/100 mesh Ottawa sand placed between metal platens; result shows significant reduction in permeability at lower concentration of 2 lb/ft2 compared to higher concentration of 4 lb/ft2. Within a unit drop in porosity, permeability declines up to 98% with 2 lb/ft2 concentration while conductivity decline of 80% and 60% observed with increased concentration of 3 lb/ft2 and 4 lb/ft2 respectively. Particle sizes analysis showed 13% fines generation at lower concentration compared to 8% at higher concentration.
Effect of particle size evaluated at different closure stress by placing the Ottawa sand (20/40 and 60/100 mesh) between metal platens shows higher crushing and proppant width reduction with higher stress. However, finer mesh (60/100) mesh shows relatively higher compaction and crushing compared to coarser sand (20/40) at each compaction pressure. Effect of particle size on conductivity evaluated using long term flow through conductivity tests with Meramec formation platens shows higher decline in conductivity with finer (60/100 mesh) sand compared to coarser (20/40 mesh sand). Compaction up to 17% observed with 20/40 sand compared to 25% compaction with 60/100 sand over the flow period of 10 days.
Experiments with different types of proppant shows higher initial permeability with ceramic proppant compared to Ottawa sand under similar conditions. Over the period of 8 days, experiment with Ottawa sand shows up to 60% fracture width reduction compared to 30% with ceramic proppant. Ceramic proppant also shows uniform distribution of embedded grains and formation extrusion. However, significant diagenetic growth is observed with ceramic proppant.
Over the life of a well, due to the production, pore pressure decreases leading to increase in effective stress on fractures. To study the effects of different stress condition on conductivity, experiments were conducted at 1500, 3000 and 7500 psi closure stress keeping all other test conditions the same. Conductivity was observed to decrease significantly at higher stress. Over the flow period of 10 days, fracture width reduces up to 50% at 7500 psi whereas up to 18% and 21% fracture width reduction observed at 1500 and 3000 psi respectively. Surface scans and SEM images shows higher degree of proppant crushing and embedment with increased closure stress. Exit brine composition also shows higher silica concentration at 7500 psi throughout the period of experiment indicating significant proppant crushing and dissolution.
Experiments with different rocks machined form Meramec, Vaca Muerta and Eagle Ford suggests higher decline in conductivity with higher clay and lower quartz content formations. Assuming the matrix permeability of (50 nd) and fracture half-length (100 ft), the dimensionless fracture conductivity (FCD) observed to decline at a very high rate and goes below 20 after 18 days in Eagle Ford, 35 days in Vaca Muerta and 75 days in Meramec
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