Search results for: Manpreet%20Kaur

Authors: Manpreet Kaur

Abstract:

When legitimate credit card users are mistakenly labelled as fraudulent in numerous financial delated applications, there are numerous ethical problems. The innovative machine learning approach we have suggested in this research outperforms the current models and shows how to model a data set for credit card fraud detection while minimizing false positives. As a result, we advise using random forests as the best machine learning method for predicting and identifying credit card transaction fraud. The majority of victims of these fraudulent transactions were discovered to be credit card users over the age of 60, with a higher percentage of fraudulent transactions taking place between the specific hours.

Keywords: automated fraud detection, isolation forest method, local outlier factor, ML algorithm, credit card

Procedia PDF Downloads 75

Authors: Dalwinder Singh, Amandeep Verma, Manpreet Kaur, Birmohan Singh

Abstract:

The detection of pre-cancerous changes using a Pap smear test of cervical cell is the important step for the early diagnosis of cervical cancer. The Pap smear test consists of a sample of human cells taken from the cervix which are analysed to detect cancerous and pre-cancerous stage of the given subject. The manual analysis of these cells is labor intensive and time consuming process which relies on expert cytotechnologist. In this paper, a computer assisted system for the automated analysis of the cervical cells has been proposed. We propose a morphology based approach to the nucleus detection and segmentation of the cytoplasmic region of the given single or multiple overlapped cell. Further, various texture and region based features are calculated from these cells to classify these into normal and abnormal cell. Experimental results on public available dataset show that our system has achieved satisfactory success rate.

Keywords: cervical cancer, cervical tissue, mathematical morphology, texture features

Procedia PDF Downloads 495

Authors: Manpreet Singh, V. P. Agrawal, Gurmanjot Singh Bhatti

Abstract:

From the last decades, there is a significant technological advancement in the field of robotics, and a number of modular self-reconfigurable robots were introduced that can help in space exploration, bucket to stuff, search, and rescue operation during earthquake, etc. As there are numbers of self-reconfigurable robots, choosing the optimum one is always a concern for robot user since there is an increase in available features, facilities, complexity, etc. The objective of this research work is to present a multiple attribute decision making based methodology for coding, evaluation, comparison ranking and selection of modular self-reconfigurable robots using a technique for order preferences by similarity to ideal solution approach. However, 86 attributes that affect the structure and performance are identified. A database for modular self-reconfigurable robot on the basis of different pertinent attribute is generated. This database is very useful for the user, for selecting a robot that suits their operational needs. Two visual methods namely linear graph and spider chart are proposed for ranking of modular self-reconfigurable robots. Using five robots (Atron, Smores, Polybot, M-Tran 3, Superbot), an example is illustrated, and raking of the robots is successfully done, which shows that Smores is the best robot for the operational need illustrated, and this methodology is found to be very effective and simple to use.

Keywords: self-reconfigurable robots, MADM, TOPSIS, morphogenesis, scalability

Procedia PDF Downloads 192

Authors: Manpreet Kaur, Amita Rani, Sanjay Kumar

Abstract:

The Internet of Things (IoT), a cyber-physical paradigm, allows a large number of devices to connect and send the sensory data in the network simultaneously. This tremendous amount of data generated leads to very high network load consequently resulting in network congestion. It further amounts to frequent loss of useful information and depletion of significant amount of nodes’ energy. Therefore, there is a need to control congestion in IoT so as to prolong network lifetime and improve the quality of service (QoS). Hence, we propose a two-level clustering based routing algorithm considering congestion score and packet priority metrics that focus on minimizing the network congestion. In the proposed Priority based Congestion Control (PBCC) protocol the sensor nodes in IoT network form clusters that reduces the amount of traffic and the nodes are prioritized to emphasize important data. Simultaneously, a congestion score determines the occurrence of congestion at a particular node. The proposed protocol outperforms the existing Packet Discard Network Clustering (PDNC) protocol in terms of buffer size, packet transmission range, network region and number of nodes, under various simulation scenarios.

Keywords: internet of things, cyber-physical systems, congestion control, priority, transmission rate

Procedia PDF Downloads 277

Authors: Harminder Kaur, Manpreet Kaur, Akanksha Kapila, Reenu

Abstract:

Schiff base with general formula H₂L was derived from condensation of o-vanillin and 3-nitro-o-phenylenediamine. This Schiff base was used for the synthesis of organotin(IV) complexes with general formula R₂SnL [R=Phenyl or n-octyl] using equimolar quantities. Elemental analysis UV-Vis, FTIR, and multinuclear spectroscopic techniques (¹H, ¹³C, and ¹¹⁹Sn) NMR were carried out for the characterization of the synthesized complexes. These complexes were coloured and soluble in polar solvents. Computational studies have been performed to obtain the details of the geometry and electronic structures of ligand as well as complexes. Geometry of the ligands and complexes have been optimized at the level of Density Functional Theory with B3LYP/6-311G (d,p) and B3LYP/MPW1PW91 respectively followed by vibrational frequency analysis using Gaussian 09. Observed ¹¹⁹Sn NMR chemical shifts of one of the synthesized complexes showed tetrahedral geometry around Tin atom which is also confirmed by DFT. HOMO-LUMO energy distribution was calculated. FTIR, ¹HNMR and ¹³CNMR spectra were also obtained theoretically using DFT. Further IRC calculations were employed to determine the transition state for the reaction and to get the theoretical information about the reaction pathway. Moreover, molecular docking studies can be explored to ensure the anticancer activity of the newly synthesized organotin(IV) complexes.

Keywords: DFT, molecular docking, organotin(IV) complexes, o-vanillin, 3-nitro-o-phenylenediamine

Procedia PDF Downloads 126

Authors: Vikrum Malhotra, Manpreet Kaur, Ayesha Ghotto

Abstract:

Background: Cardiac registries such as ACC Percutaneous Coronary Intervention Registry require high quality data to be abstracted, including data elements such as nuclear cardiology, diagnostic coronary angiography, and PCI. Introduction: The audit tool created is used by data abstractors to provide data audits and assess the accuracy and inter-rater reliability of abstraction performed by the abstractors for a health system. This audit tool solution has been developed across 13 registries, including ACC/NCDR registries, PCI, STS, Get with the Guidelines. Methodology: The data audit tool was used to audit internal registry abstraction for all data elements, including stress test performed, type of stress test, data of stress test, results of stress test, risk/extent of ischemia, diagnostic catheterization detail, and PCI data elements for ACC/NCDR PCI registries. This is being used across 20 hospital systems internally and providing abstraction and audit services for them. Results: The data audit tool had inter-rater reliability and accuracy greater than 95% data accuracy and IRR score for the PCI registry in 50 PCI registry cases in 2021. Conclusion: The tool is being used internally for surgical societies and across hospital systems. The audit tool enables the abstractor to be assessed by an external abstractor and includes all of the data dictionary fields for each registry.

Keywords: abstraction, cardiac registry, cardiovascular registry, registry, data

Procedia PDF Downloads 73

Authors: Manpreet Kaur

Abstract:

The effect of external and internal exposure in outdoor and indoor environment can be significantly gauged by natural radionuclides. Therefore, it is a consequential to approximate the level of radionuclide contents in soil samples of any area and the risks associated with it. Rate of radon emerging from soil is also one of the prominent parameters for the assessment of radon levels in environmental. In present study, natural radionuclide contents viz. ²³²Th, ²³⁸U and ⁴⁰K and radon/thoron exhalation rates were evaluated operating thallium doped sodium iodide gamma radiation detector and advanced Smart Rn Duo technique in the soil samples from 30 villages of Jammu district, Jammu and Kashmir, India. Radon flux rate was also measured by using surface chamber technique. Results obtained with two different methods were compared to investigate the cause of emanation factor in the soil profile. The radon mass exhalation rate in the soil samples has been found varying from 15 ± 0.4 to 38 ± 0.8 mBq kg⁻¹ h⁻¹ while thoron surface exhalation rate has been found varying from 90 ± 22 to 4880 ± 280 Bq m⁻² h⁻¹. The mean value of radium equivalent activity (99 ± 27 Bq kg⁻¹) was appeared to be well within the admissible limit of 370 Bq kg⁻¹ suggested by Organization for Economic Cooperation and Development (2009) report. The values of various parameters related to radiological hazards were also calculated and all parameters have been found to be well below the safe limits given by various organizations. The outcomes pointed out that region was protected from danger as per health risks effects associated with these radionuclide contents is concerned.

Keywords: absorbed dose rate, exhalation rate, human health, radionuclide

Procedia PDF Downloads 113

Authors: Supreet Singh, Manpreet Kaur, Manoj Kumar

Abstract:

High temperature corrosion is an imperative material degradation method experienced in thermal power plants and other energy generation sectors. Metallic materials such as ferritic steels have special properties such as easy fabrication and machinibilty, low cost, but a serious drawback of these materials is the worsening in properties initiating from the interaction with the environments. The metallic materials do not endure higher temperatures for extensive period of time because of their poor corrosion resistance. Friction Stir Processing (FSP), has emerged as the potent surface modification means and control of microstructure in thermo mechanically heat affecting zones of various metal alloys. In the current research work, FSP was done on the boiler tube of SA 210 Grade A1 material which is regularly used by thermal power plants. The strengthening of SA210 Grade A1 boiler steel through microstructural refinement by Friction Stir Processing (FSP) and analyze the effect of the same on high temperature corrosion behavior. The high temperature corrosion performance of the unprocessed and the FSPed specimens were evaluated in the laboratory using molten salt environment of Na₂SO₄-82%Fe₂(SO₄). The unprocessed and FSPed low carbon steel Gr A1 evaluation was done in terms of microstructure, corrosion resistance, mechanical properties like hardness- tensile. The in-depth characterization was done by EBSD, SEM/EDS and X-ray mapping analyses with an aim to propose the mechanism behind high temperature corrosion behavior of the FSPed steel.

Keywords: boiler steel, characterization, corrosion, EBSD/SEM/EDS/XRD, friction stir processing

Procedia PDF Downloads 207

Authors: Suraj Amrutkar, R. Gowri, Asma Khan, Nazam Khan, Vikas Mahajan, Manpreet Kour And Bharti Deshmukh

Abstract:

Herbal additives are rich in vitamin C, A and other biological active compounds and may act as surrogate source to subdue heat stress in chicken. Among various herbal additives such as rough lemon (Citrus Jambhiri Lush) juice, amla (Emblica officinalis) juice and aloe vera (Aloe barbadensis miller) gel are easily available during summer (stress period) and also cost less as comparison to synthetic feed additives in market. In order to analyze the performance by supplementation of rough lemon juice, amla juice and aloe vera gel in broiler under heat stress conditions. Study was carried out with a random distribution of day old straight run chicks (240 No.) in to four treatment group (n=60) was done. All the groups were given basal diet (Maize-Soya based; T0) was same for all the groups with supplementation of rough lemon juice (T1), amla juice (T2) and aloe vera (T3) @ 2% in drinking water. Experiment trial lasted for 42 days during heat stress period (June-July) with minimum THI (78.2) and Maximum THI (88.02). Feed and water were offered ad-libitum throughout the trial. Results revealed significantly higher (P<0.05) body weight in T3 and T2, followed by T1 and least in T0 at 42 days of age. The overall mean of Feed conversion ratio of various treatment T0, T1, T2 andT3 were 2.16, 1.98, 1.89 and 1.82, respectively. The mortality percentage in various treatment, T0, T1, T2 and T3, were 6.67, 3.33, 0.0 and 1.67, respectively. pH value, PCV (%), Sodium (mmol/L) and Potassium (mmol/L) was higher in T3 than rest of the groups. HL ratio is significantly lower (P<0.05) in T3, T2 followed by T1 than T0 at 42 days of age. It may be inferred that amongst these phyto-additives, aloe vera leads in alleviating heat stress in broiler in an economical way, followed by amla and rough lemon.

Keywords: rough lemon, amla, aloe vera, heat stress, broiler

Procedia PDF Downloads 51

Authors: Manpreet Kaur, Badaruddoza, Sandeep Kaur Brar

Abstract:

The increasing prevalence of adolescent obesity is one of the major causes to be hypertensive in adulthood. Various statistical methods have been applied to examine the performance of anthropometric indices for the identification of adverse cardiovascular risk profile. The present work was undertaken to determine the significant traditional risk factors through principal component factor analysis (PCFA) among population based Punjabi adolescents aged 10-18 years. Data was collected among adolescent children from different schools situated in urban areas of Punjab, India. Principal component factor analysis (PCFA) was applied to extract orthogonal components from anthropometric and physiometric variables. Association between components were explained by factor loadings. The PCFA extracted four factors, which explained 84.21%, 84.06% and 83.15% of the total variance of the 14 original quantitative traits among boys, girls and combined subjects respectively. Factor 1 has high loading of the traits that reflect adiposity such as waist circumference, BMI and skinfolds among both sexes. However, waist circumference and body mass index are the indicator of abdominal obesity which increases the risk of cardiovascular diseases. The loadings of these two traits have found maximum in girls adolescents (WC=0.924; BMI=0.905). Therefore, factor 1 is the strong indicator of atherosclerosis in adolescents. Factor 2 is predominantly loaded with blood pressures and related traits (SBP, DBP, MBP and pulse rate) which reflect the risk of essential hypertension in adolescent girls and combined subjects, whereas, factor 2 loaded with obesity related traits in boys (weight and hip circumferences). Comparably, factor 3 is loaded with blood pressures in boys and with height and WHR in girls, while factor 4 contains high loading of pulse pressure among boys, girls and combined group of adolescents.

Keywords: adolescent obesity, cvd, hypertension, punjabi population

Procedia PDF Downloads 335

Authors: Priyatma Singh, Manpreet Kaur

Abstract:

Climate change is progressively being identified as a global crisis and this has immediate repercussions for Fiji Islands due to its geographical location being prone to natural disasters. In the Pacific, it is common to find significant differences between men and women, in terms of their roles and responsibilities. In the pursuit of prudent preparedness before disasters, Fijian women’s engagement is constrained due to socially constructed roles and expectation of women here in Fiji. This vulnerability is aggravated by viewing women as victims, rather than as key people who have vital information of their society, economy, and environment, as well as useful skills, which, when recognized and used, can be effective in disaster risk reduction. The focus of this study on disaster management is to outline ways in which Fijian women can be actively engaged in disaster risk management, articulating in decision-making, negating the perceived ideology of women’s constricted roles in Fiji and unveiling social constraints that limit women’s access to practical disaster management strategic plan. This paper outlines the importance of gender mainstreaming in disaster risk reduction and the ways of mainstreaming gender based on a literature review. It analyses theoretical study of academic literature as well as papers and reports produced by various national and international institutions and explores ways to better inform and engage women for climate change per ser disaster management in Fiji. The empowerment of women is believed to be a critical element in constructing disaster resilience as women are often considered to be the designers of community resilience at the local level. Gender mainstreaming as a way of bringing a gender perspective into climate related disasters can be applied to distinguish the varying needs and capacities of women, and integrate them into climate change adaptation strategies. This study will advocate women articulation in disaster risk management, thus giving equal standing to females in Fiji and also identify the gaps and inform national and local Disaster Risk Management authorities to implement processes that enhance gender equality and women’s empowerment towards a more equitable and effective disaster practice.

Keywords: disaster risk management, climate change, gender mainstreaming, women empowerment

Procedia PDF Downloads 348

Authors: Manpreet Kaur, Cheol-Hong Min

Abstract:

The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

Procedia PDF Downloads 200