Browsing by Author "Kumar, P."
Now showing 1 - 20 of 114
- Results Per Page
- Sort Options
Item A Comprehensive Review of Brain Tumor Detection and Segmentation Techniques(Springer Science and Business Media Deutschland GmbH, 2023) Azade, A.; Kumar, P.; Kamath S․, S.Brain tumors are particularly dangerous type of tumor, and if this is not treated in time it maybe prove to be deadly and may also spread across other body parts. Brain tumor is the swelling or growth of unwanted tissues in the brain that results from the unregulated and disordered division of cells. The presence of these tissues resulting abnormal behavior and lot of other complications. The detection of brain tumor is done by using different techniques out of which through magnetic resonance images (MRIs). The scanning process is a time-consuming manual task that needs the involvement of medical professionals. Automating the task of detection of the brain tumor while also grading the severity accurately can help in managing the patients’ disease effectively. As tumor tissue of different patients is different, automating such processes is often a challenging task. Researchers have incorporated image segmentation for extraction of suspicious regions from MRI, using image processing and AI-based techniques. Radiomic analysis also plays a big role in feature extraction processes. In this paper, we present a comprehensive review of existing approaches for brain tumour detection, covering deep neural models, radiomic analysis and segmentation-based methods for brain tumor classification and segmentation, along with a discussion on prevalent issues, challenges, and future directions of research. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item A geographical location aware energy efficient routing scheme for query based Wireless Sensor Networks(2013) Kumar, P.; Chaturvedi, A.; Shrivastava, S.In this paper, a geographical location based routing scheme is proposed that works effectively for different hierarchical networks and thus supports an important aspect of network scalability. Further, herein a heuristic is proposed that minimizes the occurrence of hot spot to improve the overall life time of Wireless Sensor Networks (WSNs). This utilizes residual energy estimation based on energy of each sensor node. Its implementation mainly comprises of the geographical location of each sensor in Binary Location Index (BLI) representation form, precise updates about the link with shortest path, and coverage of the each sensor; the method which is without change of cluster head is compared with the change of cluster head based on BLI for fixed single sink.Item A Wideband Circularly Polarized Slot Antenna Backed by a Frequency Selective Surface(Korean Institute of Electromagnetic Engineering and Science, 2019) Kumar, P.; Tharehalli Rajanna, P.K.T.; Rudramuni, K.; Kandasamy, K.This paper presents the design of a coplanar waveguide (CPW)-fed single-layer wideband circularly polarized (CP) planar slot antenna backed by a frequency selective surface (FSS). The planar slot antenna is fed with a stub-loaded modified CPW feed line to tune and optimize the impedance bandwidth. The corners of the square slot antenna are perturbed to produce two orthogonal degenerate modes required for a wideband CP operation. The FSS layer is placed under the slot antenna to increase the gain and axial ratio bandwidth. The measured results of the proposed antenna provide an impedance bandwidth of 63.22% and an axial ratio bandwidth of 31.14% with a peak gain of 4.87 dB. The proposed antenna has a simple geometry, a wide CP bandwidth, and a good gain. © 2019. The Korean Institute of Electromagnetic Engineering and Science. All Rights Reserved.Item Affective Feedback Synthesis Towards Multimodal Text and Image Data(Association for Computing Machinery, 2023) Kumar, P.; Bhatt, G.; Ingle, O.; Goyal, D.; Raman, B.In this article, we have defined a novel task of affective feedback synthesis that generates feedback for input text and corresponding images in a way similar to humans responding to multimodal data. A feedback synthesis system has been proposed and trained using ground-truth human comments along with image-text input. We have also constructed a large-scale dataset consisting of images, text, Twitter user comments, and the number of likes for the comments by crawling news articles through Twitter feeds. The proposed system extracts textual features using a transformer-based textual encoder. The visual features have been extracted using a Faster region-based convolutional neural networks model. The textual and visual features have been concatenated to construct multimodal features that the decoder uses to synthesize the feedback. We have compared the results of the proposed system with baseline models using quantitative and qualitative measures. The synthesized feedbacks have been analyzed using automatic and human evaluation. They have been found to be semantically similar to the ground-truth comments and relevant to the given text-image input. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.Item An Adaptive Algorithm for Emotion Quotient Extraction of Viral Information Over Twitter Data(Springer Science and Business Media Deutschland GmbH, 2022) Kumar, P.; Reji, R.E.; Singh, V.In social media platforms, a viral information or trending term draws attention, as it asserts the impact of user content towards topic/terms. In real-time sentiment analysis, these viral terms could deliver potential insights for the analysis and decision support. A traditional sentiment analysis tool generates the level of predefined sentiments over social media content for the defined duration and lacks in the extraction of emotional impact created by the same. In these settings, it is a multifaceted task to estimate precisely the emotional quotient viral information creates. A novel algorithm is proposed, to (i) extract the sentiment and emotions quotient of current viral information over twitter, (ii) compare co-occurring trending/viral information, (iii) in-depth analysis of potential Twitter text data. The generated emotion quotients and micro-sentiment reveals several valuable insight of a viral/trending topic and assists in decision support. A use-case analysis over real-time extracted data asserts significant insights, as generated sentiments and emotional effects reveals co-relations caused by viral/trending information. The algorithm delivers an efficient, robust, and adaptable solution for the sentiment analysis also. © 2022, Springer Nature Switzerland AG.Item An energy efficient algorithm to avoid hot spot effects in Wireless Sensor Networks(IEEE Computer Society help@computer.org, 2013) Kumar, P.; Chaturvedi, A.In this paper, a novel approach is proposed to minimize the hot spot effect to improve the life time of Wireless Sensor Networks (WSNs) based on energy of each sensor node. To implement the proposed approach, the spatial locations of geographical area under surveillance are motioned using binary location index. The simulation work is carried out for two different case studies; in first case the sink/base station is remains stationary during entire observation, whereas in other case the sink is reallocated to appropriate locations at suitable time instants. Timely varying pattern of residual energy of all network nodes and total number of queries supported by entire network till it attains targeted life time is presented and discussed. © 2013 IEEE.Item An enhanced protein secondary structure prediction using deep learning framework on hybrid profile based features(Elsevier Ltd, 2020) Kumar, P.; Bankapur, S.; Patil, N.Accurate protein secondary structure prediction (PSSP) is essential to identify structural classes, protein folds, and its tertiary structure. To identify the secondary structure, experimental methods exhibit higher precision with the trade-off of high cost and time. In this study, we propose an effective prediction model which consists of hybrid features of 42-dimensions with the combination of convolutional neural network (CNN) and bidirectional recurrent neural network (BRNN). The proposed model is accessed on four benchmark datasets such as CB6133, CB513, CASP10, and CAP11 using Q3, Q8, and segment overlap (Sov) metrics. The proposed model reported Q3 accuracy of 85.4%, 85.4%, 83.7%, 81.5%, and Q8 accuracy 75.8%, 73.5%, 72.2%, and 70% on CB6133, CB513, CASP10, and CAP11 datasets respectively. The results of the proposed model are improved by a minimum factor of 2.5% and 2.1% in Q3 and Q8 accuracy respectively, as compared to the popular existing models on CB513 dataset. Further, the quality of the Q3 results is validated by structural class prediction and compared with PSI-PRED. The experiment showed that the quality of the Q3 results of the proposed model is higher than that of PSI-PRED. © 2019 Elsevier B.V.Item An experimental study on material removal rate and surface roughness of Cu-Al-Mn ternary shape memory alloys using CNC end milling(Institute of Physics, 2024) Praveen, N.; Siddeshkumar, N.G.; Prasad, C.D.; Kumar, M.; Kumar, S.; Hrishikesh, H.; Saravana Bavan, S.; Prabhu B, S.R.; Kumar, P.This study investigates the impact of Computer Numerical Control (CNC) milling parameters on Cu-Al-Mn SMAs (Shape memory alloys) to evaluate the effects on Surface Roughness (SR) and Material Removal Rate (MRR). The primary variables examined comprise of cutting speed, feed rate, and depth of cut. Results indicate that the Shape Memory Effect (SME) is higher in Copper Aluminium Manganese (CAM 3) compared to CAM 1 and CAM 2, with SME improving from 3.5% to 5.5% as Manganese (Mn) content increases, reflecting an increase in dislocations within the metal’s crystal structure. Surface roughness increases with higher feed rates and depths of cut but decreases with increased cutting speed. MRR shows a positive correlation with feed rate, depth of cut, and cutting speed, though it decreases with higher Mn content. Notably, CAM 3 exhibits lower MRR compared to CAM 1 and CAM 2. Scanning Electron Microscopy (SEM) reveals that at lower feed rates (0.10 mm rev−1), the surface is smooth and free of ridges or feed marks, while at higher feed rates (0.18 mm rev−1), noticeable surface imperfections and plastic deformation occur. The addition of Mn improves surface smoothness and machinability, it also affects MRR. Further suggesting that Mn content and milling parameters significantly influence both the mechanical properties and machinability of Cu-Al-Mn SMAs respectively. © 2024 The Author(s). Published by IOP Publishing Ltd.Item Attribute -TID method for discovering sequence of attributes(2012) Kumar, P.; Ananthanarayana, V.S.The abstraction based algorithms read databases in sequential order and then construct abstraction of the database in memory. Given any database with n attributes, it is possible to read the same in n! ways. These different n! ways lead to abstractions of different sizes. In this paper, for a given a set of transactions D, we find the sequence or order of the attributes in which the database is read, a representation which is compact than PC-tree, can be obtained in the memory. � 2012 Springer-Verlag.Item Attribute -TID method for discovering sequence of attributes(2012) Kumar, P.; Ananthanarayana, V.S.The abstraction based algorithms read databases in sequential order and then construct abstraction of the database in memory. Given any database with n attributes, it is possible to read the same in n! ways. These different n! ways lead to abstractions of different sizes. In this paper, for a given a set of transactions D, we find the sequence or order of the attributes in which the database is read, a representation which is compact than PC-tree, can be obtained in the memory. © 2012 Springer-Verlag.Item Collaborative Deadline-sensitive Multi-task Offloading in Vehicular-Cloud Networks(Institute of Electrical and Electronics Engineers Inc., 2025) Kumar, P.; Sushma, S.A.; Chandrasekaran, K.; Addya, S.K.With the growing technological advancements in the Internet and advanced functionalities in vehicular networks, it becomes crucial to execute tasks quickly and efficiently. However, the limited onboard computational capacity and vehicle mobility make it challenging to accomplish latency-sensitive tasks efficiently. Task offloading provides a promising solution to overcome these challenges. Cloud data centers provide efficient solutions, but returning the results to the vehicles takes longer due to the large physical distance. Leveraging edge servers to execute latency-sensitive tasks provides a fast, interactive response and less transmission cost. However, in a dynamic network, vehicles will be in constant motion with varying speeds, resulting in frequent handoffs from one base station to another. Our proposed work aims to select the optimal nodes to perform binary offloading with minimum cost using the collaborative vehicular network. We use a greedy-based offloading approach to address these challenges and achieve better quality-of-service and quality-of-experience in a dynamic environment to minimize costs, delay reduction ratio, and satisfaction ratio. The proposed work outperforms the baseline by 60.44%, 53.43% in reducing total system cost, delay reduction ratio, and 36% improvement in the satisfaction ratio compared to baseline algorithms. © 2025 IEEE.Item Combined effect of multidirectional forging and heat treatment on erosion and corrosion behaviour of the Mg-Zn-Mn alloys(Korean Society of Mechanical Engineers, 2024) Anne, G.; Hegde, A.; Kudva, S.A.; Sharma, P.; Kumar, P.; Matapati, M.; Ramesh, S.; Sharma, S.S.Multidirectional forging (MDF) was successfully applied to the Mg-4Zn-1Mn alloy for five passes at 300 °C. The grain size of 5 pass MDF processed samples reached 18 ± 3 µm from 256 ± 6 µm, and ?-Mg, MgZn2 and MnZn13 peaks were observed. Further MDF processed samples were solution treated (ST) at 300 °C for 2 h and quenched in SAE 20W40 oil and followed by artificial ageing (A) at 170 °C for four different timings including 1.5 h, 2 h, 2.5 h and 3.5 h respectively. The peak hardness of 219 Hv (5 pass MDF + H sample) was found in 2h artificial ageing which is 3.1 times higher compared to counterpart homogenised samples. Improvement of mechanical properties was attributed to smaller grain size and precipitation strengthening as well as distribution of the secondary phases. The combined effect of MDF and heat treatment was analysed using solid particle erosion tests at 30° and 90° impact angles using alumina. It was observed that higher impact angle (90°) had more erosion rate in all conditions and 5 pass MDF + H samples exhibited better erosion (0.0001 mg/g) due to higher hardness. On the other hand, polarisation and electrochemical impedance spectroscopy measurements were used to assess the alloys’ corrosion behaviour. The 3 pass MDF + H sample was found to have a corrosion rate of 0.0235 mm/y, which is two times lower than the counterpart 3 pass MDF processed samples and sixteen times lower than the homogenised sample (0.3838 mm/y). This was primarily due to the secondary phases’ better distribution and smaller grain size. © The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2024.Item Correction: Synthesis of BNiO3 Nanocomposites for Photocatalytic Hydrogen Production Applications (Journal of The Institution of Engineers (India): Series D, (2024), 10.1007/s40033-024-00725-5)(Springer, 2025) Choudhary, R.K.; Kumaraswamy, G.N.; Baitha, R.; Kumar, M.; Shekokar, S.R.; Kumar, A.; Hussain, M.H.; Kumar, P.In this article the affiliation details for author Rajesh Baitha was incorrectly given as ‘Department of Mechanical Engineering, Gaya College of Engineering, Gaya, India' but should have been ‘Department of Mechanical Engineering, Government Engineering College, Nawada, India’. © The Institution of Engineers (India) 2025.Item Corrosion behaviour of 18%Ni M250 grade maraging steel under welded condition in hydrochloric acid medium(2013) Kumar, P.; Nityananda, Shetty, A.The corrosion behaviour of welded maraging steel in hydrochloric acid solutions was studied over a range of acid concentration and solution temperature by electrochemical techniques like Tafel extrapolation method and electrochemical impedance spectroscopy. The corrosion rate of welded maraging steel increases with the increase in temperature and concentration of hydrochloric acid in the medium. The energies of activation, enthalpy of activation and entropy of activation for the corrosion process were calculated. The surface morphology of the corroded sample was evaluated by surface examination using scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS).Item Corrosion behaviour of 18%Ni M250 grade maraging steel under welded condition in hydrochloric acid medium(2013) Kumar, P.; Nityananda Shetty, A.N.The corrosion behaviour of welded maraging steel in hydrochloric acid solutions was studied over a range of acid concentration and solution temperature by electrochemical techniques like Tafel extrapolation method and electrochemical impedance spectroscopy. The corrosion rate of welded maraging steel increases with the increase in temperature and concentration of hydrochloric acid in the medium. The energies of activation, enthalpy of activation and entropy of activation for the corrosion process were calculated. The surface morphology of the corroded sample was evaluated by surface examination using scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS).Item Corrosion inhibition effect of 2,5-bis (3,4,5-trimethoxy phenyl)-1,3,4-oxadiazole (BTPO) on 18 Ni M250 grade welded maraging steel in 1.0 M sulphuric acid medium(2014) Kumar, P.; Shetty, A.N.Corrosion inhibition of welded maraging steel in 1.0 M sulphuric acid was studied in the presence of different concentrations of 2,5-bis (3,4,5-trimethoxy phenyl)-1,3,4-oxadiazole (BTPO) by electrochemical techniques. The results confided that BTPO was a good inhibitor, and the inhibition efficiencies obtained from potentiodynamic polarization and electrochemical impedance methods were in good agreement. The inhibitor, BTPO, acted essentially as a mixed-type inhibitor with its inhibition action through its surface adsorption. The inhibition effciency was found to increase with the increase in BTPO concentration but decreased with the increase in temperature. The activation parameters for the corrosion of the alloy and thermodynamic parameters for the adsorption of BTPO on the alloy surface were calculated and discussed. The adsorption of BTPO on welded maraging steel surface was predominantly through physisorption and obeyed the Langmuir adsorption isotherm. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) study confirmed the formation of an anticorrosion protective film of BTPO on the metal surface.Item Corrosion inhibition effect of 2,5-bis (3,4,5-trimethoxy phenyl)-1,3,4-oxadiazole (BTPO) on 18 Ni M250 grade welded maraging steel in 1.0 M sulphuric acid medium(Mohammed Premier University jmaterenvironsci@gmail.com, 2014) Kumar, P.; Nityananda Shetty, A.N.Corrosion inhibition of welded maraging steel in 1.0 M sulphuric acid was studied in the presence of different concentrations of 2,5-bis (3,4,5-trimethoxy phenyl)-1,3,4-oxadiazole (BTPO) by electrochemical techniques. The results confided that BTPO was a good inhibitor, and the inhibition efficiencies obtained from potentiodynamic polarization and electrochemical impedance methods were in good agreement. The inhibitor, BTPO, acted essentially as a mixed-type inhibitor with its inhibition action through its surface adsorption. The inhibition effciency was found to increase with the increase in BTPO concentration but decreased with the increase in temperature. The activation parameters for the corrosion of the alloy and thermodynamic parameters for the adsorption of BTPO on the alloy surface were calculated and discussed. The adsorption of BTPO on welded maraging steel surface was predominantly through physisorption and obeyed the Langmuir adsorption isotherm. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) study confirmed the formation of an anticorrosion protective film of BTPO on the metal surface.Item Dense Optical Flow using RAFT(Institute of Electrical and Electronics Engineers Inc., 2022) Khaishagi, M.A.K.; Kumar, P.; Naik, D.RAFT is a deep network architecture for the detection of optical flow in the images. The RAFT model relates the per pixel motion between images even for minor changes in the position of the objects. It also updates the flow of field through recurrent units that perform lookups on the performance of the model. RAFT also works well with different datatypes and also it has better efficiency, training speed and count of parameters. Experiments were performed by using different parameters and also by changing certain values in the model itself. One cycle learning was also used to find the best parameters for the model. We also found that the RAFT model performs better than most of the other existing models for optical flow calculation in to images. © 2022 IEEE.Item Design and analysis of microstrip elliptical low pass filter(2009) Kumar, P.; Chaturvedi, A.Design and analysis of a stepped impedance elliptical microstrip low pass filter has been described in this paper. To improve the frequency response, fractals have been proposed in the conventional design. Conventional geometry and fractalized geometry have been simulated and thus obtained results are reported and compared.