Genetic Variants of CYP11B2 and CYP1A1 Among the North-Indian Punjabi Females with Polycystic Ovary Syndrome

Ratneev Kaur,Mandeep Kaur,Sukhjashanpreet Singh,Tajinder Kaur,Anupam Kaur 대한임상검사과학회 2022 대한임상검사과학회지(KJCLS) Vol.54 No.4

Polycystic ovary syndrome (PCOS) is a complex endocrinopathy in women of reproductive age. The genetics of PCOS is heterogeneous with the involvement of number of genes in the steroid synthesis pathway. The CYP11B2 encodes aldosterone synthase and the genetic variants might increase aldosterone secretion in PCOS cases. CYP1A1 is known to enhance the intraovarian catechol estrogen production and thus the propensity for PCOS. The present case-control study analyzed a total of 619 females for CYP11B2 (rs1799998) and CYP1A1 (rs4646903) polymorphisms. Obesity was examined according to body mass index (BMI) and waist hip ratio (WHR) categorization. Biochemical (lipid profile) analysis was performed in PCOS females. BMI (P=0.0001) and WHR (P=0.0001) revealed a statistically significant difference between PCOS cases and controls. The overall levels of triglycerides were higher in PCOS females. The genotype frequency distribution of CYP11B2 (rs1799998) polymorphism revealed statistically significant difference between PCOS cases and controls (P=0.017). However, CYP1A1 (rs4646903) polymorphism did not showed any association with PCOS. The present case-control association analysis is first from our region for CYP1A1 and CYP11B2 polymorphisms and is suggestive of genetic predisposition of steroidogenic genes among PCOS patients in the North-Indian Punjabi females.

Forgery Detection Using Noise Estimation and HOG Feature Extraction

Mandeep Kaur,Savita Walia 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.4

Forgery detection techniques are required to verify the authenticity of the digital images. The additional noise is the most general way to hide the traces of the tampering done to the image. Original images which do not undergo any alterations are supposed to have a consistency in noise variation. If the image is forged, the noise no longer remains consistent throughout the image. In this paper, a method is proposed to detect the forgery based upon noise estimation and hog feature extraction. The image is first converted to YIQ colorspace, and then the block segmentation is performed on Y component of the YIQ image. Noise is estimated using PCA and hog features are extracted from each block of the image. An unsupervised clustering method is used to cluster the blocks of the image. The experimental results show that the proposed technique detects forged images more effectively as compared to previous method based only on noise estimation.

Fusion of PACE Regression and Decision Tree for Comment Volume Prediction

Mandeep Kaur,Prince Verma 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.11

The analysis of social networking sites is a vast area of research as there are tremendous measures of records showing up in online networking. Predicting the comment patterns of users on these sites is a complex decision making process. This paper proposes a hybrid model of linear regression (PACE regression) and non linear regression (REP Tree) that predicts the likelihood of the comment volume, which a post may receive by analyzing the various features of the corresponding page, post and previous records of comment patterns of users. To mechanize the procedure, a model is built comprising of the crawler, data processor and information revelation module. The new hybridized model has improved the time and space complexity along with Accuracy by building a right sized tree using only significant features with low misclassification rate.

A Novel Security Approach for Data Flow and Data Pattern Analysis to Mitigate DDOS Attacks in VANETs

Mandeep Kaur,Manish Mahajan 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.8

The VANET security is an important issue with the rise of the automatically driven vehicle based technologies. The automatically driven vehicle based clusters are programmed for each vehicle to run individually by coordinating with all of the other nodes in the VANET cluster. The proposed model has been designed to detect and mitigate the DoS and DDoS attacks in the VANET clusters to avoid any of the misbehavior or mis-happening in the form of VANET node failure, collision or in any other form. The DDoS attack prevention algorithm works as the real time attack detection and overhead data filtering algorithm in order to protect against the DoS and DDoS attacks. The proposed model result has been obtained on the basis of network load, throughput, packet delivery ratio, etc. The experimental results have proved the efficiency of the proposed model in comparison with the existing models.

Magnetoelectric Coupling in CuO Nanoparticles for Spintronics Applications

Mandeep Kaur,Alexandr Tovstolytkin,Gurmeet Singh Lotey 대한금속·재료학회 2018 ELECTRONIC MATERIALS LETTERS Vol.14 No.3

Multiferroic copper oxide (CuO) nanoparticles have been synthesized by colloidal synthesis method. The morphological,structural, magnetic, dielectric and magnetodielectric property has been investigated. The structural study reveals themonoclinic structure of CuO nanoparticles. Transmission electron microscopy images disclose that the size of the CuOnanoparticles is 18 nm and the synthesized nanoparticles are uniform in size and dispersion. Magnetic study tells the weakferromagnetic character of CuO nanoparticles with coercivity and retentivity value 206 Oe and 0.060 emu/g respectively. Dielectric study confirms that the dielectric constant of CuO nanoparticles is around 1091 at low frequency. The magnetoelectriccoupling in the synthesized CuO nanoparticles has been calculated by measuring magnetodielectric coupling coefficient.

Implementing Particle Swarm Optimization with Aging Leader and Challengers (ALC-PSO)

Er. Avneet Kaur,Er. Mandeep Kaur 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.5

In nature, the organisms have a limited lifespan and they grow older with time. Aging is an essential process which leads to the maintenance of species diversity in environment. Every group of species is lead by a leader. As the lifespan of every organism is limited, at a certain point of its life time, the organism deteriorates and become inefficient to lead its group. In this situation, a new leader is found who can efficiently lead its group. The lifespan of the leader and its leading power is checked, if it is not efficient enough, a new challenger is found to lead the group. This aging mechanism is applied to the stochastic process of Particle Swarm Optimization(PSO), in order to remove the limitations that existed in PSO such as: it gets stuck in local optima and the algorithm converges pre-maturely. When aging leader algorithm is applied to PSO, these limitations are removed in an efficient manner. This paper presents some issues that occur while designing and implementing a variant of PSO (Particle Swarm Optimization) i.e. ALC-PSO (PSO with Aging Leader and Challengers) which can highly improve the performance of PSO by applying the process of aging to the members of the swarm , bringing its members to the best position.

A Comprehensive Survey of Test Functions for Evaluating the Performance of Particle Swarm Optimization Algorithm

Er. Avneet Kaur,Er. Mandeep Kaur 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.5

Test functions play an important role in validating and comparing the performance of optimization algorithms. The test functions should have some diverse properties, which can be useful in testing of any new algorithm. The efficiency, reliability and validation of optimization algorithms can be done by using a set of standard benchmarks or test functions. For any new optimization, it is necessary to validate its performance and compare it with other existing algorithms using a good set of test functions. Optimization problems are widely used in various fields of science and technology. Sometimes such problems can be very complex. Particle Swarm Optimization is a stochastic algorithm used for solving such optimization problems. This paper transplants some of the test functions which can be used to test the performance of Particle Swarm Optimization (PSO) algorithm, in order to improve its performance and have better results. Different test functions can be used for different types of problems. These test functions have a specific range and values, which can be applied in different situations. These functions, when applied to the PSO algorithm, can give the better comparison of results. The test functions that have been the most commonly adopted to assess performance of PSO-based algorithms and details of each of them are provided, such as the search range, the position of their known optima, and other relevant properties.

High Capacity, Reversible Data Hiding Using CDCS Along with Medical Image Authentication

Amrinder Singh Brar,Mandeep Kaur 보안공학연구지원센터(IJSIP) 2015 International Journal of Signal Processing, Image Vol.8 No.1

Healthcare institution that handles a number of patients, opinions is often sought from different experts. It demands the exchange of the medical history of the patient among the experts which includes the medical images, prescriptions and electronic patient records (EPR) etc. In order to reduce storage and transmission cost, data hiding techniques are used to embed patient information with medical images. In medical imaging applications, there are stringent constraints on image fidelity that strictly prohibit any permanent image distortion by the watermarking or data hiding. Authenticity is another important aspect in medical image watermarking. This paper proposed modified difference expansion watermarking using LSB replacement in the difference of virtual border for data hiding in medical images. The Class Dependent Coding Scheme (CDCS) is used to encode the EPR data so that embedding capacity can be increased. The image hash is calculated using MD5 to provide authentication. Experimental results show that proposed scheme provide us large data hiding capacities along with very high PSNR values as compared to earlier EPR data hiding techniques.

Development of protein tyrosine phosphatase 1B (PTPIB) Inhibitors from marine sources and other natural products-Future of Antidiabetic Therapy : A Systematic Review

KAUR, Kulvinder Kochar,ALLAHBADIA, Gautam,SINGH, Mandeep Korea FoodHealth Convergence Association 2019 식품보건융합연구 (KJFHC) Vol.5 No.3

The incidence of both obesity and Type 2 Diabetes Mellitus( DM) is increasing proportionately so that causes of deaths from these has overtaken from that of malnourishment. Hence it has been recommended to treat the 2 in parallel considering the role of diabesity on health. Important causes of T2DM are insulin resistance (IR) and /or inadequate insulin secretion. Protein tyrosine phosphatase 1B(PTPIB) has a negative impact in insulin signaling pathways and hence plays crucial role inT2DM,since its overexpression might induce IR. Thus PTPIB is considered a therapeutic target for both obesity and T2DM, there has been a search for novel ,promising natural inhibitors. We conducted a pubmed search for articles related to PTPIB inhibitors from natural causes be it marine sources or other natural sources. Out of 988 articles we selected 100 articles for review. Thus various bioactive molecules isolated from marine organisms that can acts as PTPIB Inhibitors and thus possess antidiabetic activity both in vitro/ in vivo studies ,besides products from fruits like Chinese raspberry or curcumin used as routine spices are described with their chemical classes, structure-activity relationships and potency as assessed by IC 50 values are discussed. More work is required to make this a reality.

Study of Effect on Performance of DE/BBO on Changing Parametric Values

Ekta,Mandeep Kaur 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.5

DE\BBO is the hybridization of Differential Evolution optimization and Biogeography Based Optimization. DE is considered to have good exploration ability and BBO is considered to have good exploitation ability, to achieve goodness of both techniques, these techniques have been combined. Hybridization of Differential evaluation and biogeography based optimization dominates the performance of biogeography based optimization. The influencing factors of performance of DE are scaling factor and cross-over rate which are used to track proper optimization. In this paper, it has been shown how DE/BBO outperforms BBO. The change in the performance of DE/BBO due to variation in some pre-considered variables has also been highlighted. It has been observed that DE/BBO performs best when scaling factor is 0.11 and cross over rate is 0.2.