Search results for: Madhurima Poddar

Authors: Madhurima Poddar, Vinay Sharma, Shaikh M. Mobin, Rajneesh Misra

Abstract:

Three 1,8-naphthalimide (NPI) substituted 4,4-difluoroboradiaza-s-indacene (BODIPY) dyads were synthesized via Pd-catalyzed Sonogashira cross-coupling reaction of ethynyl substituted NPI with the meso-, β- and α-halogenated BODIPYs, respectively. The photophysical and electrochemical data reveals considerable electronic communication between the BODIPY and NPI moieties. The electronic absorption spectrum reveals that the substitution of NPI at α position of BODIPY exhibit better electronic communication between the NPI and the BODIPY units. The electronic structures of all the dyads exhibit planar geometries which are in a good correlation with the structures obtained from single crystal X-ray diffraction. The crystal structures of the dyads exhibit interesting supramolecular interactions. The dyads show good cytocompatibility with the potential of multicolor live-cell imaging; making them excellent candidates for biological applications. The work provides an important strategy of screening the substitution pattern at different position of BODIPYs which will be useful for the design of BODIPY based organic molecules for various optoelectronic applications as well as bio-imaging.

Keywords: bio-imaging studies, cross-coupling, cyclic voltammetry, density functional calculations, fluorescence spectra, single crystal XRD, UV/Vis spectroscopy

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Authors: Rakesh Krishna, Abhishek Poddar

Abstract:

The paper discusses the work carried out on the implementation of control techniques like Digital Pulse Width Modulation (PWM) and Digital Pulse Fired control(PFC). These techniques are often used in devices like inverters, battery chargers, DC-to-DC converters can also be implemented on household devices like heaters. The advantage being the control and improved life span of device. In case of batteries using these techniques are known to increase the life span of battery in mobiles and other hand-held devices. 8051 microcontroller is used to implement these methods.Thyristors are used for switching operations.

Keywords: PWM, SVM, PFC, bidirectional inverters, snubber

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Authors: Madhurima S. Waghmare, Shaleen Singhal

Abstract:

The concept of smartness, inclusion, sustainability is multidisciplinary and fuzzy, rooted in economic and social development theories and policies which get reflected in the spatial development of the cities. It is a challenge to convert these concepts from aspirations to transforming actions. There is a dearth of assessment and planning tools to support the city planners and administrators in developing smart, inclusive, and sustainable cities. To address this gap, this study develops an inclusive cities decision matrix based on an exploratory approach and using mixed methods. The matrix is soundly based on a review of multidisciplinary urban sector literature and refined and finalized based on inputs from experts and insights from case studies. The application of the decision matric on the case study cities in India suggests that the contemporary planning tools for cities need to be multidisciplinary and flexible to respond to the unique needs of the diverse contexts. The paper suggests that a multidimensional and inclusive approach to city planning can play an important role in building sustainable smart cities.

Keywords: inclusive-cities decision matrix, smart cities in India, city planning tools, sustainable cities

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Authors: Alebachew Halefom, Navsal Kumar, Arunava Poddar

Abstract:

The purpose of this work is to specify the parameter values, the base flow index (BFI), and to rank the methods that should be used for base flow separation. Three different digital graphical approaches are chosen and used in this study for the purpose of comparison. The daily time series discharge data were collected from the site for a period of 30 years (1986 up to 2015) and were used to evaluate the algorithms. In order to separate the base flow and the surface runoff, daily recorded streamflow (m³/s) data were used to calibrate procedures and get parameter values for the basin. Additionally, the performance of the model was assessed by the use of the standard error (SE), the coefficient of determination (R²), and the flow duration curve (FDC) and baseflow indexes. The findings indicate that, in general, each strategy can be used worldwide to differentiate base flow; however, the Sliding Interval Method (SIM) performs significantly better than the other two techniques in this basin. The average base flow index was calculated to be 0.72 using the local minimum method, 0.76 using the fixed interval method, and 0.78 using the sliding interval method, respectively.

Keywords: baseflow index, digital graphical methods, streamflow, Emba Madre Watershed

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Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

Abstract:

The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

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Authors: Shreya Poddar

Abstract:

Legal drafting and revising are recognized as highly demanding tasks for legal professionals. This paper introduces an approach to automate and refine these processes through the use of advanced Artificial Intelligence (AI). The method employs Large Language Models (LLMs), with a specific focus on 'Chain of Thoughts' (CoT) and knowledge injection via prompt engineering. This approach differs from conventional methods that depend on comprehensive training or fine-tuning of models with extensive legal knowledge bases, which are often expensive and time-consuming. The proposed method incorporates knowledge injection directly into prompts, thereby enabling the AI to generate more accurate and contextually appropriate legal texts. This approach substantially decreases the necessity for thorough model training while preserving high accuracy and relevance in drafting. Additionally, the concept of guardrails is introduced. These are predefined parameters or rules established within the AI system to ensure that the generated content adheres to legal standards and ethical guidelines. The practical implications of this method for legal work are considerable. It has the potential to markedly lessen the time lawyers allocate to document drafting and revision, freeing them to concentrate on more intricate and strategic facets of legal work. Furthermore, this method makes high-quality legal drafting more accessible, possibly reducing costs and expanding the availability of legal services. This paper will elucidate the methodology, providing specific examples and case studies to demonstrate the effectiveness of 'Chain of Thoughts' and knowledge injection in legal drafting. The potential challenges and limitations of this approach will also be discussed, along with future prospects and enhancements that could further advance legal work. The impact of this research on the legal industry is substantial. The adoption of AI-driven methods by legal professionals can lead to enhanced efficiency, precision, and consistency in legal drafting, thereby altering the landscape of legal work. This research adds to the expanding field of AI in law, introducing a method that could significantly alter the nature of legal drafting and practice.

Keywords: AI-driven legal drafting, legal automation, futureoflegalwork, largelanguagemodels

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