Disparity line utilization factor based optimal placement of IPFC for congestion management

Recently, due to the adoption of power reforms, there is a marked increase of contracted power that flows in the transmission line and also the spontaneous power exchanges leading to complex power transmission congestion problems. The appearance of Flexible AC Transmission Systems (FACTS) devices specifically Interline Power Flow Controller (IPFC) has opened up new opportunities to overcome the congestion problem by increasing the possible system load. Hence, the optimal placement of FACTS devices is deservedly an issue of great importance. This paper proposes a Disparity Line Utilization Factor (DLUF) for the optimal placement of IPFC to control the congestion in transmission lines. DLUF determines the difference between the percentage MVA utilization of each line connected to the same bus. The proposed method is implemented for IEEE–14 and IEEE-57 bus test system. The IPFC is placed in all possible line combinations of IEEE-14 bus system to check the validity of the proposed methodology. To confirm the generality of the proposed method, the technique is also implemented and verified for IEEE-57 bus test system. An increased load of 110% and 125% is applied, and the results are presented and analysed in detail to establish the effectiveness of the proposed methodology

Outcome of locking compression plate fixation in the management of distal end femur fractures: one year hospital based study

Background: Distal femur fractures make up 6 to 7% of all femur fractures. Various plating options for distal femur fracture are conventional buttress plates, fixed-angle devices, and locking plates. This study was planned to evaluate and explore locking compression plate fixation in distal end femur fractures which is expected to provide a stable fixation with minimum exposure, early mobilization, less complications and a better quality of life.Methods: The study was conducted as prospective clinical study in 20 skeletally mature patients with x-ray evidence of distal femur fracture fulfilling inclusion and exclusion criteria, operated with distal femur LCP plating. Patients were assessed radiologically and classified according to distal femur fracture classification and outcome graded as excellent, good, fair and poor based on Lysholm Knee Score.Results: Out of 15 excellent outcome cases, 3 cases were type A1 fracture, 1 case had type A3, 2 cases had type B1 and B2 each, 5 cases had type C2 and 2 cases had type C3 fracture. 1 case with good outcome was type C3. 1 case with fair outcome was type B2. While 3 cases with poor outcome were type A1, A2 and C3.Conclusions: The DF-LCP is an ideal implant to use for fractures of the distal femur. However, accurate positioning and fixation are required to produce satisfactory results. We recommend use of this implant in Type A and C, osteoporotic and periprosthetic fractures

Tip Speed Ratio Based MPPT Algorithm and Improved Field Oriented Control for Extracting Optimal Real power and Independent Reactive Power Control for Grid Connected Doubly Fed Induction Generator

Doubly Fed Induction Generator (DFIG) needs to get adopted to change in wind speeds with sudden change in reactive power or grid terminal voltage as it is required for maintaining synchronism and stability as per modern grid rules. This paper proposes a controller for DFIG converters and optimal tip speed ratio based maximum power point tracking (MPPT) for turbine to maintain equilibrium in rotor speed, generator torque, and stator and rotor voltages and also to meet desired reference real power during the turbulences like sudden change in reactive power or voltage with concurrently changing wind speed. The performance of DFIG is compared when there is change in wind speed only, changes in reactive power and variation in grid voltage along with variation in wind speed

Management of displaced patella fracture with modified tension band wiring and percutaneous cannulated screws-a dilemma

Background: Displaced patella fracture has seen various surgical management methods in the past among which tension band wiring (TBW) and less invasive percutaneous cannulated cancellous (CC) screw  fixation are mostly preferred and debated on which is better option. The study has been designed to compare the functional outcome and various parameters of both the methods.Methods: The study was conducted as prospective clinical study in 30 skeletally mature patients with x-ray evidence of patella fracture fulfilling inclusion and exclusion criteria, out of which 15 were done tension band wiring and rest percutaneous cancellous screw and outcome graded as excellent, good, fair and poor based on Lysholm knee score.Results: The comparison of the mean values of the Lysholm score in patients operated with patella TBW (92.47) were better than with percutaneous CC screw fixation (88.93). Patella TBW was responsible for all the cases of infection 2 (6.67%) and delayed non-union 1 (3.33%). Whereas stiff was nearly equal in both the techniques. The comparison of the mean values of the knee flexion in patients operated by using percutaneous CC screw (107.27) was better than patella TBW (105.67).Conclusions: Patients managed with CC screw fixation technique achieved better knee function, especially in the early postoperative period. The reported advantages of the percutaneous fixation technique include avoidance of extended incisions, preservation of the blood supply to the patella, and the possibility of a simpler removal of all hardware in the clinical setting. These results suggest that the percutaneous CC screw technique may be a superior alternative to conventional modified tension band wiring

Fundamental noise dynamics in cascaded-order Brillouin lasers

The dynamics of cascaded-order Brillouin lasers make them ideal for applications such as rotation sensing, highly coherent optical communications, and low-noise microwave signal synthesis. Remark- ably, when implemented at the chip-scale, recent experimental studies have revealed that Brillouin lasers can operate in the fundamental linewidth regime where optomechanical and quantum noise sources dominate. To explore new opportunities for enhanced performance, we formulate a simple model to describe the physics of cascaded Brillouin lasers based on the coupled mode dynamics governed by electrostriction and the fluctuation-dissipation theorem. From this model, we obtain analytical formulas describing the steady state power evolution and accompanying noise properties, including expressions for phase noise, relative intensity noise and power spectra for beat notes of cascaded laser orders. Our analysis reveals that cascading modifies the dynamics of intermediate laser orders, yielding noise properties that differ from single-mode Brillouin lasers. These modifications lead to a Stokes order linewidth dependency on the coupled order dynamics and a broader linewidth than that predicted with previous single order theories. We also derive a simple analytical expression for the higher order beat notes that enables calculation of the Stokes linewidth based on only the relative measured powers between orders instead of absolute parameters, yielding a method to measure cascaded order linewidth as well as a prediction for sub-Hz operation. We validate our results using stochastic numerical simulations of the cascaded laser dynamics.Comment: 18 pages, 9 figure

Technology for Kisan Samanvayam: Nutrition Intelligibility of Groundnut Plant using IoT-ML Framework

Neolithic Demographic transition resulting the reduction of habitable land for cultivation. Hence the smart agriculture is the only way to cater higher food demand. The farming community of developing countries like India needs Kisan Samanvayam with futuristic technologies for financially viable cultivation. Technology place vital role in economically nourishment of soil fertility and crop management. In this regard we proposed IoT-ML framework for remotely assessing the soil nutrients (N, P,K), PH and early stage detection of crop deceases. Android APP which is a part and parcel of the frame work enable the farmer to have real time visual statistics of the soil nutrients, notifications and suggestions regarding to the crop management. JXCT Soil NPK sensors, PH sensors, Dual Core ESP32 Controllers, Firebase Cloud and Random Forest Decision Tree machine Learning Algorithm, Micromlgen serve this purpose. Unlike Solitary sensor for entire field, we have divided a hector into four subregions for effective monitoring local region needs. The presence of IoT with TinyML increased the robustness of the framework and results are encouraging with sandy loam soil

A Model of Motion Processing in the Visual Cortex Using Neural Field With Asymmetric Hebbian Learning

Neurons in the dorsal pathway of the visual cortex are thought to be involved in motion processing. The first site of motion processing is the primary visual cortex (V1), encoding the direction of motion in local receptive fields, with higher order motion processing happening in the middle temporal area (MT). Complex motion properties like optic flow are processed in higher cortical areas of the Medial Superior Temporal area (MST). In this study, a hierarchical neural field network model of motion processing is presented. The model architecture has an input layer followed by either one or cascade of two neural fields (NF): the first of these, NF1, represents V1, while the second, NF2, represents MT. A special feature of the model is that lateral connections used in the neural fields are trained by asymmetric Hebbian learning, imparting to the neural field the ability to process sequential information in motion stimuli. The model was trained using various traditional moving patterns such as bars, squares, gratings, plaids, and random dot stimulus. In the case of bar stimuli, the model had only a single NF, the neurons of which developed a direction map of the moving bar stimuli. Training a network with two NFs on moving square and moving plaids stimuli, we show that, while the neurons in NF1 respond to the direction of the component (such as gratings and edges) motion, the neurons in NF2 (analogous to MT) responding to the direction of the pattern (plaids, square object) motion. In the third study, a network with 2 NFs was simulated using random dot stimuli (RDS) with translational motion, and show that the NF2 neurons can encode the direction of the concurrent dot motion (also called translational flow motion), independent of the dot configuration. This translational RDS flow motion is decoded by a simple perceptron network (a layer above NF2) with an accuracy of 100% on train set and 90% on the test set, thereby demonstrating that the proposed network can generalize to new dot configurations. Also, the response properties of the model on different input stimuli closely resembled many of the known features of the neurons found in electrophysiological studies

Nurturing Agribusiness: A Sustainable Farming System for Tomato Crop Management Leveraging Machine Learning

The agriculture industry is undergoing a transformative shift with the introduction of IoT technology, enabling global connectivity for farmers. This technology offers a plethora of advantages, ranging from precise seed selection based on soil analysis to efficient crop maintenance, water management, and enhanced marketing support for improved profitability. To further enhance tomato farming practices, we propose the implementation of a smart farmer marketing assistant that streamlines the process of segregating yield based on its growth stage, reducing labor and time requirements.Further, the frame work is capable of early-disease management system that can detect  diseases like early blight,light blight, buck eye rot and anthranose and suggest remedy.  By adopting this innovative approach, financial losses associated with traditional methods are minimized.The traditional practice of combining all categories of vegetables (ripened, unripened, and partially rotten) in a single container often results in reduced shelf life for the produce. In our framework, we employ color sorting to categorize the vegetables, ensuring proper packing into their respective bins. This valuable data is made accessible through a cloud environment, providing potential buyers with comprehensive information about the yield, its category, and pricing. This increased visibility empowers farmers to reach a global market and sell their produce at competitive prices. In this context, we present a case study focused on the tomato crop, where we have successfully developed a prototype utilizing ESP32, a color sensor, and Google Firebase. This comprehensive framework effectively harnesses the power of IoT, Machine Learning, and potential marketing strategies, transforming the way farmers manage their crops and connect with buyers on a global scale with highly accurate 87.9% experimental results

Modeling the development of cortical responses in primate dorsal (“where”) pathway to optic flow using hierarchical neural field models

Although there is a plethora of modeling literature dedicated to the object recognition processes of the ventral (“what”) pathway of primate visual systems, modeling studies on the motion-sensitive regions like the Medial superior temporal area (MST) of the dorsal (“where”) pathway are relatively scarce. Neurons in the MST area of the macaque monkey respond selectively to different types of optic flow sequences such as radial and rotational flows. We present three models that are designed to simulate the computation of optic flow performed by the MST neurons. Model-1 and model-2 each composed of three stages: Direction Selective Mosaic Network (DSMN), Cell Plane Network (CPNW) or the Hebbian Network (HBNW), and the Optic flow network (OF). The three stages roughly correspond to V1-MT-MST areas, respectively, in the primate motion pathway. Both these models are trained stage by stage using a biologically plausible variation of Hebbian rule. The simulation results show that, neurons in model-1 and model-2 (that are trained on translational, radial, and rotational sequences) develop responses that could account for MSTd cell properties found neurobiologically. On the other hand, model-3 consists of the Velocity Selective Mosaic Network (VSMN) followed by a convolutional neural network (CNN) which is trained on radial and rotational sequences using a supervised backpropagation algorithm. The quantitative comparison of response similarity matrices (RSMs), made out of convolution layer and last hidden layer responses, show that model-3 neuron responses are consistent with the idea of functional hierarchy in the macaque motion pathway. These results also suggest that the deep learning models could offer a computationally elegant and biologically plausible solution to simulate the development of cortical responses of the primate motion pathway