26 research outputs found
Stabilizer Design for a Two Area Power System Network
No full textA power system stabilizer is an ancillary device used for improving stability of otherwise poorly stable power system. It helps to restore the system back to the operating point after disturbances like load changes or faulty situations are withdrawn or smoother transition from one to another operating point. Originally, power system stabilizers are installed to add damping to local oscillatory modes, which were destabilized by high gain, fast acting exciters. Its property is to provide damping torque to reduce the electromechanical oscillations introduced in the system under disturbances. We analyze the small signal stability for a power system using linearized model and design a stabilizer for single machine infinite bus system. Then the study is extended for a two area system where small signal and transient stability for both intra-area and inter-area modes is observed. The simulation is performed using MATLAB package, SIMULINK and Power System Toolbox (PST)
Advancing Sugarcane Disease Detection through CNN-Based Deep Learning
No full textAgriculture produce especially sugarcane crop is no exception to diseases as compared to the other crops. Sugarcane, a vital cash crop for the global sugar industry, faces numerous challenges, with the Top Borer disease. Disease prone sugarcane crop directly affects the production quality and quantity. Sugarcane infections are a cause of worry for the farmers because they can wipe out the entire crop field. Researchers are working on applying Artificial Intelligence (AI) techniques, like Machine Learning (ML) and Deep Learning (DL), to analyse the agricultural data (yield prediction, selling price forecasting, climate, and soil quality etc.) and prevent crop damage due to various reasons, diseases being one of them. Deep neural network which includes Convolutional Neural Network (CNN) is a modern technique for agricultural disease detection. Hence, this paper presents the feasibility study and the effectiveness of DL based CNN algorithm in the disease detection of crops with special reference to selective four diseases of sugarcane crop in India. The proposed system integrates state-of-the-art deep learning algorithms, leveraging Convolutional Neural Networks (CNNs) and recurrent models, to analyze high-resolution images captured by unmanned aerial vehicles (UAVs) or ground-based sensors. These images provide a comprehensive view of the sugarcane plantation, allowing for the identification of subtle symptoms and early-stage infections that may go unnoticed by the human eye. The key components of the developed system include a robust image preprocessing pipeline to enhance the quality of input data, a customized deep neural network architecture trained on a diverse dataset of sugarcane images, and a real-time monitoring system for timely intervention. The model's performance is evaluated on a large-scale dataset collected from sugarcane plantations across diverse geographic regions. The results demonstrate the system's high accuracy in detecting and classifying the Top Borer disease, outperforming traditional methods
ब्रिटिशकालीन हरियाणा में सामाजिक-धार्मिक सुधार आन्दोलन : एक अध्ययन
No full textप्रस्तुत शोध पत्र में ब्रिटिश भारत में हुए सामाजिक-धार्मिक सुधार आंदोलनों पर प्रकाश डाला गया है। ब्रिटिश शासन काल में पाश्चात्य शिक्षा प्राप्त लोगों ने सामाजिक रचना, धर्म, रीति-रिवाज व परम्पराओं को तर्क की कसौटी पर कसना प्रारम्भ कर दिया। इससे भारत में सामाजिक एवं धार्मिक सुधार आंदोलनों का जन्म हुआ। भारतीय समाज को पुनर्जीवन प्रदान करने का प्रयत्न प्रबुद्ध भारतीय सामाजिक एवं धार्मिक सुधारकों, सुधारवादी, ब्रिटिश गवर्नर जनरलों एवं आधुनिक शिक्षा के प्रसार ने किया। भारत में समाज और धर्म हमेशा एक दूसरे से जुडे रहे हैं और यहाँ की समाजिक परम्पराएं और रुढियां का आधार धार्मिक व्याख्या है। अतः सामजिक परिवर्तन और सुधार के लिए यह आवश्यक था कि धार्मिक मूल्यों और मान्यताओं की तर्कपूर्ण व्याख्या की जाये ताकि उसके आधार पर समाज में वांछित सुधार किया जा सके। यही कारण है कि भारत में समाजिक और धार्मिक सुधार आंदोलन एक साथ ही चले। शोध पत्र में इसके विकास, कारणों और हरियाणा क्षे़त्र में हुए परिवर्तनों का परीक्षण किया गया है।
केन्द्र बिन्दु : हरियाणा, आर्य समाज, सिंह सभा, वेदांत, पुनर्जागर
Impact of Application Methods and Doses of Micronutrients on Wheat’ Grain Yield, Nutrient Content and Their Uptake
No full textVarious methodologies (soil or foliar application) and doses of zinc (Zn), iron (Fe) and manganese (Mn) either in conjunction with urea or in combination with one another were used to evaluate grain and straw production as well as nutrient concentration and their uptake in wheat. The experiment\u27s findings showed that adding Zn, Fe and Mn significantly enhanced grain and straw production over control as well as available nitrogen (N), phosphorus (P) and potassium (K) content and their uptake. When 2.5 mg Zn kg-1 + 5 mg Fe kg-1 + 5 mg Mn kg-1 + 30 mg N kg-1 was applied, the maximum grain yield, straw yield, P uptake in grain and straw, as well as K concentration and uptake in grain and straw were found. Highest N content both in grain and straw was observed when 0.5% FeSO4 + 3 % Urea were applied. Phosphorus content in grain was recorded highest when 0.5% MnSO4 + 0.5% Citric acid was applied whereas in straw maximum concentration of phosphorus was noticed when 0.5% ZnSO4 + 2% Urea were applied. Highest uptake of nitrogen in grain was found when 0.5% MnSO4 + 2.5% Urea were applied and in straw when 0.5% FeSO4 + 3 % Urea were applied. The experimental results also showed that micronutrient (Zn, Fe and Mn) concentration and uptake significantly increased as compared to control with micronutrient application (Zn, Fe and Mn)
Influence of Zinc, Iron and Manganese Applications on Soil Properties, Protein Content and Sedimentation Value of Wheat
No full textMicronutrient insufficiency in plants is becoming increasingly common, particularly in cereals crops around the world. These deficits result in a loss of yield as well as deterioration in the nutritional quality of the crops. The experiment was carried out in screen house for Rabi season of 2017-18, Soil Science Department, CCS HAU, Hisar to measure the impact of methods and dosages of zinc (Zn), iron (Fe) and manganese (Mn) application on post-harvest soil characteristics and wheat quality. The findings of this research illustrated that DTPA-extractable Zn and Mn increased significantly with the addition of Zn and Mn, respectively as compared to control. With the application of micronutrients, the sedimentation value and protein content of wheat both significantly increased in comparison to the control. Maximum increase in sedimentation value (54.0) was found when 0.5 % ZnSO4 + 2.5 % urea was applied. Whereas, maximum increase in protein content (12.2%) was observed when 0.5 % FeSO4 + 3 % urea was applied. Overall, quality of wheat improved with the application of micronutrients but there was no significant effect of these applications on soil parameters. There was no significant variation in soil pH, soil organic carbon (SOC), electrical conductivity (EC), available nitrogen (N), phosphorus (P), potassium (K) and DTPA-extractable Fe when micronutrients were applied as foliar or basal doses
Characterization and Classification of Sugarcane Growing Soil of Haryana, India
No full textEight representative pedons of sugarcane growing soil of Haryana viz., Damla, Yamunanagar (P1), Shahabaad, Kurukshetra (P2), RRS, Karnal (P3), Kaithal (P4), Mehlana, Sonipat (P5), Nidhani, Jind (P6), Mokhra, Rohtak (P7) and Meham, Rohtak (P8) were studied for morphological, physico-chemical characteristics and classified as per Soil Taxonomy. The colour of the studied pedons varied from yellowish brown (10YR 3/2) to dark brown (10YR 5/5) in colour, with dominant hue of 10YR. The range of bulk density of different horizons was 1.05 to 1.33 Mg m-3. These soils were slightly alkaline to moderately alkaline in reaction. The soils of all the pedons of studied area were non saline in nature having EC < 1.36 dSm-1. Exchangeable Sodium percentage (ESP) and Base Saturation Percentage (BSP) ranged from 1.65 to 47.55 % and 23.18 to 99.60 % respectively. The CEC of the soils ranged from 1.98 to 13.82 cmol (p+) kg-1. The soils of the area were classified according to Soil Taxonomy as Fine loamy, Mixed, Hyperthermic, Typic Ustocrepts (Pedon 3,6 and 7), Fine loamy, Calcareous, Mixed, Hyperthermic, Typic Haplustepts (pedon-4), Fine loamy, Mixed, Hyperthermic, Typic Haplustepts (pedon-2), Coarse loamy, Mixed, Hyperthermic, Aquic Ustochrepts (pedon-5) and Coarse loamy, Mixed, Hyperthermic, Typic Haplustepts (1 and 8)
A Globally Convergent Gradient-based Bilevel Hyperparameter Optimization Method
No full textHyperparameter optimization in machine learning is often achieved using naive
techniques that only lead to an approximate set of hyperparameters. Although
techniques such as Bayesian optimization perform an intelligent search on a
given domain of hyperparameters, it does not guarantee an optimal solution. A
major drawback of most of these approaches is an exponential increase of their
search domain with number of hyperparameters, increasing the computational cost
and making the approaches slow. The hyperparameter optimization problem is
inherently a bilevel optimization task, and some studies have attempted bilevel
solution methodologies for solving this problem. However, these studies assume
a unique set of model weights that minimize the training loss, which is
generally violated by deep learning architectures. This paper discusses a
gradient-based bilevel method addressing these drawbacks for solving the
hyperparameter optimization problem. The proposed method can handle continuous
hyperparameters for which we have chosen the regularization hyperparameter in
our experiments. The method guarantees convergence to the set of optimal
hyperparameters that this study has theoretically proven. The idea is based on
approximating the lower-level optimal value function using Gaussian process
regression. As a result, the bilevel problem is reduced to a single level
constrained optimization task that is solved using the augmented Lagrangian
method. We have performed an extensive computational study on the MNIST and
CIFAR-10 datasets on multi-layer perceptron and LeNet architectures that
confirms the efficiency of the proposed method. A comparative study against
grid search, random search, Bayesian optimization, and HyberBand method on
various hyperparameter problems shows that the proposed algorithm converges
with lower computation and leads to models that generalize better on the
testing set
Systemic Variety of Anaplastic Large - Cell Lymphoma
No full textWe present a case report of a patient with very aggressive course of anaplastic large-cell lymphoma. The patient had nonspecific complaints of easy fatigability and progressive breathlessness and had generalized lymphadenopathy. Initial investigations revealed pancytopenia. Bone marrow examination revealed presence of atypical cells. Liver biopsy showed portal tracts infiltrated by atypical lymphoid cells. Fine-needle aspiration of the lymph node finally confirmed anaplastic large-cell lymphoma. Patient succumbed to the illness
Sports Specific Influence on Force Vital Capacity in University Players
No full textAbstract: Objective
Effect of Cryo-Deformation on Aging Characteristics of Age-Hardenable Aluminium Alloys
No full textThe effect of plastic deformation by cryo-rolling on the microstructural evolution and aging characteristics of an Al-Zn-Mg alloy was investigated employing DSC, hardness measurements and TEM/EDAX. Specimens were water quenched after a solution heat-treatment, cryo-rolled upto - 90% deformation, short annealed and aged in 3 different temper conditions. The specimens aged under T6 condition have attained peak hardness with faster precipitation kinetics, during the second step of aging, i.e. at 150oC with in 1 to 3h, the time required being inversely proportional to the amount of deformation. The microstructure consisted of ultra-fine grains with size ranging between 100-250nm. This also resulted in finer precipitates of strengthening particles
