DeepFuse: A Deep Unsupervised Approach for Exposure Fusion with Extreme Exposure Image Pairs

We present a novel deep learning architecture for fusing static multi-exposure images. Current multi-exposure fusion (MEF) approaches use hand-crafted features to fuse input sequence. However, the weak hand-crafted representations are not robust to varying input conditions. Moreover, they perform poorly for extreme exposure image pairs. Thus, it is highly desirable to have a method that is robust to varying input conditions and capable of handling extreme exposure without artifacts. Deep representations have known to be robust to input conditions and have shown phenomenal performance in a supervised setting. However, the stumbling block in using deep learning for MEF was the lack of sufficient training data and an oracle to provide the ground-truth for supervision. To address the above issues, we have gathered a large dataset of multi-exposure image stacks for training and to circumvent the need for ground truth images, we propose an unsupervised deep learning framework for MEF utilizing a no-reference quality metric as loss function. The proposed approach uses a novel CNN architecture trained to learn the fusion operation without reference ground truth image. The model fuses a set of common low level features extracted from each image to generate artifact-free perceptually pleasing results. We perform extensive quantitative and qualitative evaluation and show that the proposed technique outperforms existing state-of-the-art approaches for a variety of natural images.Comment: ICCV 201

Mathematical Modeling and Simulation of Photovoltaic Cell using Matlab-Simulink Environment

Photovoltaic power supplied to the utility grid is gaining more and more visibility while the world’s powers demand is increases. Growing demand, advancements in semiconductor technology and magnetic materials such as high frequency inductor cores, has a significant impact on PV inverter topologies and their efficiencies, on the improvement of the control circuits on the potential of costs reduction. The user naturally wants to operate the Photovoltaic (PV) array at its highest energy conversion output by continuously utilizing the maximum available solar power of the array. The electrical system PV modules are powered by solar arrays requires special design considerations due to varying nature of the solar power generated resulting from unpredictable and sudden changes in weather conditions which change the solar irradiation level as well as the cell operating temperature. This paper, a mathematical model of a Photovoltaic (PV) cell used matlab-simulink environment, is developed and presented. The model is developed using basic circuit equations of the photovoltaic solar cells including the effects of solar irradiation and temperature changes. The main objective is to find the parameters of the nonlinear I–V equation by adjusting the curve at three points: open circuit, maximum power, and short circuit. the method finds the best I–V equation for the single-diode photovoltaic (PV) model including the effect of the series and parallel resistances–  Key words : Photovoltaic system (PV), maximum power, PV array,PV cellDOI:http://dx.doi.org/10.11591/ijece.v2i1.11

Future prediction of Population, Birth and Fertility rates in India

Background: Fertility rates have been declining worldwide over the past fifty years, part of a phenomenon known as “the demographic transition”. Aims & Objectives: To draw on life history theory to examine the relationship between population density and fertility rate in India over 74 years. Material &Methods: The association between population versus Birth rate and population versus fertility rate was found using Correlation Analysis, to fit the models using Least square methods. Results: A robust association was found between population and fertility rate, population and Birth rate over the analyzed time period. Population, Birth rate, and Fertility rate for one decade were also forecasted using the best least square method. Conclusion: The analysis shows that the population is on an increasing trend and the Birth rate and fertility rate have decreased tendency

Modeling and Analysis of PFC with Appreciable Voltage ripple to achieve Fast Transient Response

The design of an active Power Factor Corrector (PFC) leads to slow transient response in this type of converter. The reason for this  is due to  compensator placed in the output-voltage feedback loop is frequently designed to have narrow bandwidth to filter the voltage ripple of twice the line frequency obtaining from the PFC output voltage. This feedback loop is designed with this filtering effect because a relatively high ripple would cause considerable distortion in the reference line current feedback loop and line current. However, if the bandwidth of the compensator in the voltage loop is relatively wide, the transient response of the PFC range is improved. As a significance of the voltage ripple at the output of the compensator, both the static and the dynamic behaviors of the PFC change in comparison with no voltage ripple on the control signal. This paper presented, the static behavior of a PFC with appreciable voltage ripple in the output-voltage feedback loop using two parameters: the amplitude of the relative voltage ripple (k) on the control signal and its phase lag angle ( ).The total power processed by the PFC depends on these parameters, which do not vary with the load and which determine the Total Harmonic Distortion (THD) and the Power Factor (PF) at the input of the power factor correction converter. Finally, the results are verified by MATLAB/ Simulink simulation. Key words: Modeling, AC-DC boost converter, PFC controller, Power supplies

Assessment of relationship between Hemoglobin and BMI levels in female college students and influence of diet and physical activity on these parameters

Anaemia and nutritional status through Body Mass Index (BMI) are two key indicators in National Family Health Survey of India. The objective of the study is to determine the correlation between Hemoglobin (Hb) and BMI values and to understand the effect of diet and physical activity on these two parameters amongst college girl students. A questionnaire covering food habits and physical activity of 200 female students (18-22 years age) was used for data analysis along with Hb and BMI values of the same subjects. No significant association was found between Hb and BMI values, but a significant association was found between physical activity and BMI. Diet consumption which included leafy and other vegetarian diet, eggs and meat has shown significant contribution for high Hb levels. The present study strongly provides evidence based conclusion for the relationship between diet, nutrition and Hb levels as well physical activity and BMI. A multiple regression model was developed to estimate Hb levels based on their food habits

External Auditor Dealing With Deep Cyber Security of Open Networks

We focus on how you can release major updates to that customer as much as possible, and we suggest a new model called Cloud Storage Audit with verifiable outsourcing for major updates. Within this model, major updates can be outsourced safely to authorized parties, so the important thing throughout the customer is that downloading the update is being saved very little. Moreover, the design gives us the ability to verify the validity of the encrypted secret keys issued by the OA. Specifically, we employ external auditors in current general audit designs; allow it to act as a delegated party in our position, and is also responsible for secure audits and major key updates to resist key detection. When the cloud downloads new files, the client should download the encrypted password only in OA. The licensed party maintains the encrypted secret key from the client for cloud storage audit and updates the encrypted status every time. The client downloads the encrypted password to the authorized authority and encrypts it exactly as it would like to upload new files to the cloud. In our design, only the agriculture authority should keep the encrypted form of the customer's secret key. In our design, only the agriculture authority should keep the encrypted form of the customer's secret key. We formalize the meaning and type of security in this form

In – vitro anti tubercular activity of flowers of Couroupita guanensis L

Modern civilization is facing hundreds of disorders associated with microorganisms. The natural phytochemicals from non-edible plants are gaining importance to fight against these disease The intention of this study is to evaluate the ethanol and dichloromethane extracts of flower of Couroupita guianensis (Lecithydaceae) for anti-tubercular activity. The anti-tubercular activity of all the extracts of Couroupita guianensishave been evaluated against Mycobacterium tuberculosis H73Rv strain using Microplate Alamar Blue Assay (MABA). The activity was documented within MIC range of 0.8 to 100μg/ml. The results of MABA showed that both ethanol and dichloromethane extract exhibited significant anti-tubercular activity. The present investigation suggests that Couroupita guianensis possess remarkable anti-tubercular activit

GR-450 Enhancing Sarcasm Detection with Context Sensitivity

Sarcasm identification is a vital challenge in natural language processing. In this project, we address this challenge by employing a context-sensitive approach that leverages deep learning, transformer learning, and conventional machine learning models. We conducted our research using two benchmark datasets: Twitter and Internet Argument Corpus (IAC-v2). Our three primary models—Bi-LSTM with GloVe embeddings, BERT, and feature fusion—outperformed baseline methods, achieving an 89.4% highest accuracy on Twitter datasets and an 81.2% highest precision on IAC-v2. These results highlight the effectiveness of our approach in sarcasm detection, with significant implications for sentiment analysis and opinion mining. While our project provides promising results on benchmark datasets, further testing on live tweet datasets is essential to validate its real-world predictive capabilities. This project contributes to the ongoing efforts to enhance communication understanding in the digital era