Showing papers by "Amit Singh published in 2019"

An approach for de-noising and contrast enhancement of retinal fundus image using CLAHE

Abstract: Now-a-days medical fundus images are widely used in clinical diagnosis for the detection of retinal disorders. Fundus images are generally degraded by noise and suffer from low contrast issues. These issues make it difficult for ophthalmologist to detect and interpret diseases in fundus images. This paper presents a noise removal and contrast enhancement algorithm for fundus image. Integration of filters and contrast limited adaptive histogram equalization (CLAHE) technique is applied for solving the issues of de-noising and enhancement of color fundus image. The efficacy of the proposed method is evaluated through different performance parameters like Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), Correlation coefficient (CoC) and Edge preservation index (EPI). The proposed method achieved 7.85% improvement in PSNR, 1.19% improvement in SSIM, 0.12% improvement in CoC and 1.28% improvement in EPI when compared to the state of the art method.

Multi-layer security of medical data through watermarking and chaotic encryption for tele-health applications

Abstract: In this paper, we present a robust and secure watermarking approach using transform domain techniques for tele-health applications. The patient report/identity is embedding into the host medical image for the purpose of authentication, annotation and identification. For better confidentiality, we apply the chaos based encryption algorithm on watermarked image in a less complex manner. Experimental results clearly indicated that the proposed technique is highly robust and sufficient secure for various forms of attacks without any significant distortions between watermarked and cover image. Further, the performance evaluation of our method is found better to existing state-of-the-art watermarking techniques under consideration. Furthermore, quality analysis of the watermarked image is estimated by subjective measure which is beneficial in quality driven healthcare industry.

Survey of robust and imperceptible watermarking

Abstract: Robustness, imperceptibility and embedding capacity are the preliminary requirements of any watermarking technique. However, research concluded that these requirements are difficult to achieve at same time. In this paper, we review various recent robust and imperceptible watermarking methods in spatial and transform domain. Further, the paper introduces elementary concepts of digital watermarking, characteristics and novel applications of watermark in detail. Furthermore, various analysis and comparison of different notable watermarking techniques are discussed in tabular format. We believe that our survey contribution will helpful for fledgling researchers to develop robust and imperceptible watermarking algorithms for various practical applications.

Robust and distortion control dual watermarking in LWT domain using DCT and error correction code for color medical image

Abstract: This paper presents lifting wavelet transform (LWT) and discrete cosine transform (DCT) based robust watermarking approach for tele-health applications. For identity authentication, ‘signature watermark’ of size ‘64 × 64’ and ‘patient report’ of size ‘80’ characters are hiding into the host medical image. Further, the signature watermark is encrypted by message-digest (MD5) and ‘patient report’ is encoded by BCH error correcting code before embedding into the host image. Experimental demonstrations indicate that the method provides sufficient robustness and security against various attacks without significant distortion between cover and watermarked image. Further, our results proved that the method offer NC value more than 0.9214 for most of the considered attacks. Furthermore, it is evident from results our method shows the improvement in robustness to previously reported techniques under consideration while providing low computational complexity.

Targeting redox heterogeneity to counteract drug tolerance in replicating Mycobacterium tuberculosis

Abstract: The capacity of Mycobacterium tuberculosis (Mtb) to tolerate multiple antibiotics represents a major problem in tuberculosis (TB) management. Heterogeneity in Mtb populations is one of the factors that drives antibiotic tolerance during infection. However, the mechanisms underpinning this variation in bacterial population remain poorly understood. Here, we show that phagosomal acidification alters the redox physiology of Mtb to generate a population of replicating bacteria that display drug tolerance during infection. RNA sequencing of this redox-altered population revealed the involvement of iron-sulfur (Fe-S) cluster biogenesis, hydrogen sulfide (H2S) gas, and drug efflux pumps in antibiotic tolerance. The fraction of the pH- and redox-dependent tolerant population increased when Mtb infected macrophages with actively replicating HIV-1, suggesting that redox heterogeneity could contribute to high rates of TB therapy failure during HIV-TB coinfection. Pharmacological inhibition of phagosomal acidification by the antimalarial drug chloroquine (CQ) eradicated drug-tolerant Mtb, ameliorated lung pathology, and reduced postchemotherapeutic relapse in in vivo models. The pharmacological profile of CQ (Cmax and AUClast) exhibited no major drug-drug interaction when coadministered with first line anti-TB drugs in mice. Our data establish a link between phagosomal pH, redox metabolism, and drug tolerance in replicating Mtb and suggest repositioning of CQ to shorten TB therapy and achieve a relapse-free cure.

Quantization based multiple medical information watermarking for secure e-health

Abstract: In this paper, an improved wavelet based medical image watermarking algorithm is proposed. Initially, the proposed technique decomposes the cover medical image into ROI and NROI regions and embedding three different watermarks into the non-region of interest (NROI) part of the transformed DWT cover image for compact and secure medical data transmission in E-health environment. In addition, the method addressing the problem of channel noise distortion may lead to faulty watermark by applying error correcting codes (ECCs) before embedding them into the cover image. Further, the bit error rates (BER) performance of the proposed method is determined for different kind of attacks including ‘Checkmark’ attacks. Experimental results indicate that the Turbo code performs better than BCH (Bose-Chaudhuri-Hochquenghem) error correction code. Furthermore, the experimental results validate the effectiveness of the proposed framework in terms of BER and embedding capacity compared to other state-of-the-art methods. Therefore, the proposed method finds potential application in prevention of patient identity theft in e-health applications.

Physicochemical investigations of zinc oxide nanoparticles synthesized from Azadirachta Indica (Neem) leaf extract and their interaction with Calf-Thymus DNA

Abstract: Zinc oxide nanoparticles (ZnONps) have been extensively explored for various biological applications because of their characteristic biocompatibility, antimicrobial activity and wound healing. Green synthesis is an environment friendly alternate as compared to chemical synthesis, hence ZnONps using Azadirachta Indica (Neem) leaf extract have been synthesized in this study. ZnONps were then characterized using different analytical techniques including UV–Visible spectroscopy, FTIR, XRD, SEM, FESEM and EDAX. Interaction studies of ZnONps with Calf-Thymus DNA (CT-DNA) have further been investigated utilizing UV–Visible, UV-thermal, Fluorescence, Circular Dichroism spectroscopy and agarose gel electrophoresis. ZnONps exhibited a sharp peak around 368 nm in absorption spectra, confirming their synthesis. The surface morphology of ZnONps was examined by SEM & FESEM and the size was found in range 20–40 nm. After correlating all data, interaction of CT-DNA with ZnONps suggested the stabilization of DNA. These physicochemical investigations could further give insights for biosensing and biomedical applications.

Quality-by-Design Concepts to Improve Nanotechnology-Based Drug Development

Abstract: The purpose of this review is to discuss the challenges associated with the development of nanoparticle-based quality drug products in adhering to the principles of quality by design (QbD) and defining appropriate quality parameters towards successful product development. With the advent of nanotechnology into the pharmaceutical field, the novel field of nanomedicine was born. Due to their unique properties in terms of size, conformation and targeted delivery, nanomedicines are able to overcome many drawbacks of conventional medicine. As nano-sized formulations have made their way into more and more therapies, it has became clear that these very unique properties create hurdles for nanomedicines in successfully traversing the regulatory pathways and there is a need to develop nanomedicines in a more controlled and consistent fashion. The elements of a QbD methodology explained in this review enable the development of nano-based formulations in a way that maximizes the possibility of success. The identification of critical quality attributes (CQA) of the drug product and its intermediates are discussed in detail with a focus on nanomaterial-based formulations. In conclusion, QbD and the identification and specification of CQAs at its core are critical to the design, development and growth of nanomaterials in pharmaceuticals.

Fabrication and Validation of a Handheld Non-Invasive, Optical Biosensor for Self-Monitoring of Glucose Using Saliva

Abstract: We report the method for fabrication and validation of a standalone handheld optical biosensor for non-invasive monitoring of glucose using saliva. For this, a biodegradable, low-cost test strip for glucose was developed by co-immobilizing glucose oxidase enzyme and bromocresol purple pH sensitive dye. The enzymatic reaction produced pH change and, thus, a change in color of a filter paper strip, which was detected by a standalone electronic meter. The in-house developed meter consisted of an optically isolated region in the chassis for inserting the test strip along with the sample to avoid interferences from ambient wind and light. The developed biosensor had a wide detection range of detection between 32- and 516-mg/dL glucose concentration while the sensitivity of detection was 1.0 mg/dL/count at a limit of detection (LOD) of 32 mg/dL within a response time of 15 s. The device along with strips was validated on clinical samples while comparing salivary glucose level with that of blood glucose level using a commercial glucometer. A very good correlation was found for diabetic individuals (0.80), whereas it was less significant (0.53) for non-diabetic individuals. The device passed Clarke’s error grid analysis and hence should be medically acceptable. This simple and low-cost setup should be ideally suited for mass screening of diabetes, apart from being used as a self-monitoring device in a non-invasive and painless manner.

De-noising of ultrasound image using Bayesian approached heavy-tailed Cauchy distribution

Abstract: Medical ultrasound images are used in clinical diagnosis and generally degraded by speckle noise. This makes difficulty in automatic interpretation of diseases in ultrasound images. This paper presents a speckle removal algorithm by modeling the wavelet coefficients. A Bayesian approach is implemented to find the noise free coefficients. Cauchy prior and Gaussian Probability Density Function (PDF) are used to model the true wavelet coefficients and noisy coefficients respectively. A Maximum a Posteriori (MAP) estimator is used to estimate the noise free wavelet coefficients. A Median Absolute Deviation (MAD) estimator is used to find the variance of affected wavelet coefficients in finest scale. The proposed method is compared with existing denoising methods. The experimental results show that the method offer up to 21.48% enhancement in Peak Signal to Noise Ratio (PSNR), 1.82% enhancement in Structural Similarity Index (SSIM), 1% enhancement in Correlation coefficient (ρ) and 7.68% enhancement in Edge Preserving Index (EPI) than best existing wavelet modeling method. The results indicate that the proposed method outperforms over existing methods, both in noise reduction and edge preservation.

Combining Mexican hat wavelet and spread spectrum for adaptive watermarking and its statistical detection using medical images

Abstract: This paper present a secure medical image watermarking technique applying spread-spectrum concept in wavelet transform domain is proposed. In the first step, discrete wavelet transform(DWT) decomposes the cover medical image into four frequency sub-bands using Mexican hat as mother wavelet and then corresponding to each pixel of the binary watermark a pair of Pseudo-Noise (PN) is embedded into a horizontal (HL) and a vertical (LH) sub-band. In order to maintain the imperceptibility of the watermarked image, strength of the generated PN sequence pair is adjusted according to specified document to watermark ratio (DWR). For the extraction the watermark, statistical profile of DWT coefficients of watermarked image is determined and the obtained probability distribution function (pdf) is utilized for designing the watermark detection procedure. Proposed detector considers the best fitted Cauchy statistical model of heavy-tailed family, which accurately models the non-Gaussian DWT coefficients of an image. The robustness of the method is examined for various kinds of attacks with varying watermark to document ratio. Further, experimental results show that the proposed technique offer more robustness than other state-of-the-art method.

Enhanced sustained release of furosemide in long circulating chitosan-conjugated PLGA nanoparticles.

Abstract: Furosemide (FSM) is commonly used in the treatment of edema associated with congestive cardiac failure, cirrhosis of the liver, renal disease, including the nephrotic syndrome and hypertension. However, in ascites, it is clinically limited due to its frequent dosing and short biological half-life and its prolonged-release preparations are not available. Therefore, the main objective behind the present research work is to develop chitosan coated and conjugated poly (lactic-co-glycolic acid) (PLGA) nanocarriers, to sustain the delivery of FSM with improved systemic circulation. Emulsion-solvent evaporation technique was used for the preparation of nanoparticles. In-vivo pharmacokinetic study showed 2.6, 3.10, and 4.30 folds enhancement in relative availability of FSM for FSM-PLGA, FSM-chitosan-coated-PLGA and FSM-chitosan-conjugated- PLGA nanoparticles, respectively than FSM. The present research work concluded that FSM loaded chitosan conjugated PLGA nanoparticles could enhance the systemic circulation of FSM with improved pharmacokinetics parameters.

Fast-Acting Small Molecules Targeting Malarial Aspartyl Proteases, Plasmepsins, Inhibit Malaria Infection at Multiple Life Stages

Abstract: The eradication of malaria remains challenging due to the complex life cycle of Plasmodium and the rapid emergence of drug-resistant forms of Plasmodium falciparum and Plasmodium vivax. New, effective, and inexpensive antimalarials against multiple life stages of the parasite are urgently needed to combat the spread of malaria. Here, we synthesized a set of novel hydroxyethylamines and investigated their activities in vitro and in vivo. All of the compounds tested had an inhibitory effect on the blood stage of P. falciparum at submicromolar concentrations, with the best showing 50% inhibitory concentrations (IC50) of around 500 nM against drug-resistant P. falciparum parasites. These compounds showed inhibitory actions against plasmepsins, a family of malarial aspartyl proteases, and exhibited a marked killing effect on blood stage Plasmodium. In chloroquine-resistant Plasmodium berghei and P. berghei ANKA infected mouse models, treating mice with both compounds led to a significant decrease in blood parasite load. Importantly, two of the compounds displayed an inhibitory effect on the gametocyte stages (III-V) of P. falciparum in culture and the liver-stage infection of P. berghei both in in vitro and in vivo. Altogether, our findings suggest that fast-acting hydroxyethylamine-phthalimide analogs targeting multiple life stages of the parasite could be a valuable chemical lead for the development of novel antimalarial drugs.

Low memory block tree coding for hyperspectral images

Abstract: Hyperspectral image sensors are resource constrained and have limited on-board memory. Processing of high volume hyperspectral images pose a challenge to the memory and resources of the sensor. Contemporary wavelet based image compression schemes have intensive memory requirement of which 3D-WBTC have superior coding performance due to through the exploitation of the inter sub-band & intra sub-band redundancy. This paper presents a low memory implementation of 3D-WBTC which is a listless scheme by using the fixed size state memory to keep track of block set partitioning and significance testing of wavelet coefficients of transformed hyperspectral images. Memory access time is significantly reduced due to the elimination of lists that leads to reduced complexity. Simulation results of the proposed scheme shows that proposed coder is fast and have very low memory requirement thereby making it a suitable candidate for implementation in resource constrained hyper spectral image sensor.

Raman spectroscopy reveals distinct differences between two closely related bacterial strains, Mycobacterium indicus pranii and Mycobacterium intracellulare.

Abstract: A common technique used to differentiate bacterial species and to determine evolutionary relationships is sequencing their 16S ribosomal RNA genes. However, this method fails when organisms exhibit high similarity in these sequences. Two such strains that have identical 16S rRNA sequences are Mycobacterium indicus pranii (MIP) and Mycobacterium intracellulare. MIP is of significance as it is used as an adjuvant for protection against tuberculosis and leprosy; in addition, it shows potent anti-cancer activity. On the other hand, M. intracellulare is an opportunistic pathogen and causes severe respiratory infections in AIDS patients. It is important to differentiate these two bacterial species as they co-exist in immuno-compromised individuals. To unambiguously distinguish these two closely related bacterial strains, we employed Raman and resonance Raman spectroscopy in conjunction with multivariate statistical tools. Phenotypic profiling for these bacterial species was performed in a kinetic manner. Differences were observed in the mycolic acid profile and carotenoid pigments to show that MIP is biochemically distinct from M. intracellulare. Resonance Raman studies confirmed that carotenoids were produced by both MIP as well as M. intracellulare, though the latter produced higher amounts. Overall, this study demonstrates the potential of Raman spectroscopy in differentiating two closely related mycobacterial strains. Graphical abstract.

Image Processing Based Automated Glaucoma Detection Techniques and Role of De-Noising: A Technical Survey

Abstract: This chapter presents a detailed study of the image processing steps to identify glaucoma including the key role of the de-noising in the detection of Glaucoma. De-noising plays an important role in the area of medical imaging. One of the major applications of image processing is detection of retinal diseases. Further, important diagnostic parameters to detect glaucoma are discussed in detail. Several techniques with different diagnostic parameters are used to detect glaucoma. Image acquisition is the first step in this detection process. Existing noise in the medical image may degrade the accuracy of the detection. Therefore a preprocessing step is highly required before the commencement of actual processing. In general, optical coherence tomography (OCT) and Ultrasound retinal image are corrupted by speckle noise. The speckle noise removal techniques are reviewed. The popular de-speckling approaches are classified into different groups and a brief overview is provided. The application of these de-noising methods outperforms in diagnosing the progression of glaucoma.

Enhancement and De-Noising of OCT Image by Adaptive Wavelet Thresholding Method

Abstract: This chapter proposed an adaptive wavelet thresholding method for enhancement and de-noising of retinal optical coherence tomography (OCT) image. Speckle noise degrades the OCT image and affects the disease diagnostic utility. OCT image enhancement is required for accurate analysis of inter and intra retinal layers. Enhancement is achieved through histogram mapping called Gaussianization transform. Further wavelet coefficients are modeled statistically to get the signal and noise information for finding the threshold value for weighing the wavelet coefficients. A Cauchy distribution is used to model the wavelet coefficients. An adaptive soft thresholding is used to estimate the true wavelet coefficients. Gaussianization transform widen the intensity range and enhances the OCT image and de-noising performances. Through different performance parameters, it is demonstrated that the proposed method outperforms the state-of-the-art methods. The proposed de-noising method has achieved 4.67% improvement in Peak Signal-to-Noise Ratio (PSNR), 2.61% in Structural Similarity (SSIM), 1.33% in Correlation coefficient (CoC) and 9.4% in Edge Preservation Index (EPI) parameters than the adaptive soft thresholding method, designed without statistical modeling.

Risk-Adjusted Analysis of Patients Undergoing Emergency Laparotomy Using POSSUM and P-POSSUM Score: A Prospective Study.

Abstract: Background: Comparison of operative morbidity rates after emergency laparotomy between units may be misleading because it does not take into account the physiological variables of patients' conditions. Surgical risk scores have been created, and the most commonly used is the Physiological and Operative Severity Score for the enumeration of Mortality (POSSUM) or one of its modifications, the Portsmouth-POSSUM (P-POSSUM), usually requires intraoperative information. Objective: The objective of this study is to evaluate the POSSUM and P-POSSUM scores in predicting postoperative morbidity and mortality in patients undergoing emergency laparotomy. Methodology: This is a prospective, cross-sectional, and hospital-based study that was conducted at J.L.N. Medical College and Hospital, Ajmer, Rajasthan, India, from April 2017 to December 2017. Adult patients who presented at the causality and underwent emergency laparotomy were included in the study. Observed and predicted mortality and morbidity were calculated using POSSUM and P-POSSUM equations, and statistical significance was calculated using Chi-square test. Results: A total of 100 patients were included in this study, with a mean age of 42.83 ± 18.21 years. The observed (O) mortality was 12 (12.0%), while POSSUM predicted 40 (40%) and P-POSSUM 27 (27%). The O/E ratio for POSSUM was 0.29 and for P-POSSUM was 0.44, and this means that they both overestimate mortality. When the results were tested by Chi-square test, the P value was found to be 0.55 and 0.85 for POSSUM and P-POSSUM, respectively, which showed no significant correlation for observed and expected mortality. The observed morbidity was 69 (69%), while POSSUM expected morbidity was 79 (79%), O/E ratio is 0.87, and this again overestimates the morbidity. POSSUM is overpredicting the rate of morbidity, and test of correlation showed no significance with P = 0.75. Conclusion: POSSUM and P-POSSUM were found to overestimate mortality and morbidity in our patient's population.

The duration of intra-abdominal hypertension and increased serum lactate level are important prognostic markers in critically ill surgical patient's outcome: A prospective, observational study

Abstract: Aim: The present study analyzed the clinical significance of duration of intra-abdominal hypertension (IAH) associated with increased serum lactate in critically ill patients with severe sepsis. Materials and Methods: Our study was an observational, prospective study carried out in the Surgical Intensive Care Unit (ICU) at J.L.N Medical College, Ajmer, Rajasthan, India. In our study, we included a total of 100 patients and intra-abdominal pressure (IAP) was measured through intravesical route at the time of admission and after 6, 12, 24, 48, and 72 h via a urinary catheter filled with 25 ml of saline. Duration of ICU and hospital stay, need for ventilator support, initiation of enteral feeding, serum lactate level at time of admission and after 48 h, and 30-day mortality were noted as outcomes. Results: In our study, an overall incidence of IAH was 60%. Patients with cardiovascular surgery and renal and pulmonary dysfunction were 93.3%, 55%, and 60%, respectively, at the time of admission and 65%, 10%, and 10%, respectively, after 72 h of admission in the surgical ICU. Nonsurvivors had statistically significant higher IAP and serum lactate levels than survivors. Patients with longer duration of IAH had longer ICU and hospital stay, longer duration of vasopressors and ventilator support, and delayed enteral feeding. Conclusion: There is a strong relationship “risk accumulation” between duration of IAH associated with increased serum lactate and organ dysfunction. The duration of IAH was an independent predictor of 30-day mortality. Early recognition and prompt intervention for IAH and severe sepsis are essential to improve the patient outcomes.

Revealing carbon mediated luminescence centers with enhanced lifetime in porous alumina

Abstract: Carbon ion implantation mediated blue photoluminescence (PL) and the corresponding bluish white phosphorescence of anodic aluminum oxide (AAO) are presented. In particular, the observed 465 nm luminescence is found to be more sensitive to carbon, while its lifetime is raised to its maximum from 6.7 to 10.4 μs at a fluence of 1 × 1016 ions/cm2. The observed phenomenon seems to be associated with the formation of oxygen vacancy (V0) via carbon ion enhanced modification of local AlO6 octahedral symmetry, as revealed from X-ray absorption spectroscopy at O-K edge, and also consistent with X-ray photoelectron spectroscopy (XPS). Detailed XPS analysis indicates the preference of carbon at the Al sites, rather than at O for both octahedral and tetrahedral structures, and form CAl cationic impurity, consistent with our density functional theory calculation. Further, carbon ion implantation driven enhanced PL lifetime is shown to be associated with energy transfer between V0 and the vicinal CAl. This work shows the potential of carbon doped AAO as a future candidate for developing rare earth free nontoxic phosphor.

Efficient Generation of Association Rules from Numeric Data Using Genetic Algorithm for Smart Cities

Abstract: Machine learning plays an important role to develop smart cities by gathering real time information using several state of the art algorithms. In the recent past, association rule mining plays an important role in the discovery of accurate information from databases to satisfy the need of real time applications in smart cities ranging from healthcare to intelligent transport systems. It is used in various applications for decision making, detection and prediction etc. because of its robustness to derive associations among various attributes of datasets. This technique seems to be simple in case of categorical data but becomes quite complex in case of numeric data. In this work, we have mainly concentrated on the problem of generating association rules from numeric data in an efficient way. For accomplishing this task we have taken genetic algorithm as the base of the solution to this problem. Genetic algorithm is selected for this task because of its nature of self-improving and ability to handle large solution set. Here we have proposed genetic algorithm based association rule mining algorithm which generates random association rules on the basis of general property of datasets. The generated rule set is improved at each run of algorithm and filtered for more and more interesting and accurate rules.

Bioremediation of Municipal Wastewater and Biodiesel Production by Cultivation of Parachlorella kessleri-I

Abstract: The continuous growth of human population, industrialization and urbanization has led to the increased release of pollutants into the environment. The water pollutants are chemically toxic compounds causing harmful effect on human and animal health. Algae are effective in reducing the nutrients and toxic compound from contaminated water reservoirs, and the process is known as bioremediation. The microalgae can play a crucial role in producing the bioenergy if integrated with the remediation of wastewater while growing biomass for biofuel feedstock. This article lays emphasis on the dual role of a robust oleaginous marine microalga Parachlorella kessleri-I, which is substantial in bioremediating the wastewater and producing biofuel feedstock.

Bring your own hand: how a single sensor is bringing multiple biometrics together

Abstract: In spite of innumerable benefits of multi-biometry authentication, a couple of imaging sensors are required to capture multi-biometric samples, but that increase the overall cost as well as degree of user cooperation. This work presents a single sensor-based multimodal biometric identification system by fusing major finger knuckle, minor finger knuckle, palm print and handprint features of the human hand for enhancing the security and privacy of any consumer device. A virtual imaging device has been suggested to capture palmer and dorsal view of hand with single-shot multi-trait acquisition mechanism. The hand images captured from digital camera are first preprocessed to get the major knuckle, minor knuckle and palm ROI’s. The finger knuckles and palm print ROI’s are then enhanced and transformed to illumination invariant representation using robust encoding techniques, over which ray tracing features are emphasized predominantly. A non-rigid multi-scale approach, namely deep matching, has been employed to obtain the matching score between the corresponding correlation maps for finger knuckle or palm print recognition. Apart from that, we present a new scheme to extract shape, and geometrical features of handprint and employ metric learning-based L2-norm for feature matching in $$2D^{2}{} \textit{PCA}+2D^{2}{} \textit{LDA}$$ space. Five publicly available databases are used to evaluate the effectiveness of proposed approach. Finally, the score-level weighted sum rule fusion has been adopted to combine matching scores of four traits which show that the proposed method outperforms other unimodal and state-of-the-art multimodal identification methods in terms of EER (0.01%), DI (3.64) and CRR (100%).

Seasonal incidence of fruit fly on Summer squash (Cucurbita pepo L.) and effect of weather parameters on population dynamics of fruit fly Bactrocera cucurbitae (Coquillett)

Abstract: In the present experiment, Green victory Methyl Eugenol (ME) fruit fly traps were used to determine the seasonal incidence of fruit fly for 2017-2018 and further effect of weather parameters on population dynamics of fruit fly Bactrocera cucurbitae (Coquillett) was obtained. The studies revealed that, for seasonal incidence the fruit fly was found damaging and remained active on summer squash attaining peak value in the 26 Standard week (317 fruitflies/trap). The correlation studies showed that the fruit fly population was highly significant and positively correlated with mean relative morning humidity, relative evening humidity and rainfall but highly negatively correlated with maximum temperature.