EFFECT OF DIFFERENT LEVELS OF SOLUBLE FERTILIZERS ON NUTRIENT UPTAKE IN SOLANUM MELONGENA L.

Field investigation was carried out to study the influence of quality parameters and nutrient uptake of brinjal hybrids due to application of various levels of water soluble fertilizer. Foliar spray of NPK (19:19:19) at 0.5 per cent and 1% along with 100 and 75% recommended dose of NPK (200:150:100 kg ha-1) with 5 and 7 sprays, each starting from 30 DAT at 10 d interval, formed twenty treatments in two hybrids. Results showed that among the two different concentrations of foliar applied nutrients, 7 sprays of 1% NPK (19:19:19) along with 100 per cent recommended dose of fertilizer (200:150:100 kg ha-1) recorded the ascorbic acid content, total soluble solids (TSS) and total phenol content. Uptake of major nutrients was found to be the highest due to foliar application of 1 per cent water soluble fertilizer (7 sprays) along with 100 per cent recommended dose of fertilizer

Uniform accelerated motions

An Affine matrix which maps an initial and final pose can be computed by solving a system of linear equations. Then there exists an interesting problem of finding a time varying affinity which maps the given set of poses and if it exists is always unique and should hold some interesting properites such as affine-invariant, reversible, preserve rigidity, similarities and volume. The Steady Affine Motions and Morphs (SAM) introduced by Jarek Rossignac and Alvar Vinacua solved this problem of time varying affinity and defines the quality of such affinity by the term steadiness. Until SAM, no mathematical definition of steadiness was available and intuitively SAM defined a steady animation to be continuous, to vary dimensions and angles monotonically and rather uniformly, and to move points along pleasing arcs that are free of unnecessary kinks or loops. The authors defined the term ”Steady” as a constant velocity motion in the local moving frame. SAM creates pleasing in-betweening motions that interpolates between an initial and final pose, B and C and the derived equation of beauty was At B with A = C B·-1. SAM is affine-invariant, reversible, preserves isometries (i.e., rigidity), similarities and volume. Previously proposed approaches came up with a solution for the time varying affinity problem, but there was no proper definition of how beautiful or how good the motion was. With the advent of SAM, the beauty of a motion can now be measured by the unsteadiness and Steady Affine motions and morphs is the one solution which comes to have a value of zero for the unsteadiness term. Uniform Accelerated Motions (UAM) carries forward the above definition of steadiness into a constant acceleration motion in the local moving frame. The time varying affinity At is computed using closed form expressions and some of its interesting properties are studied. The constant acceleration motion (in local frame) in UAM is then compared with the constant velocity motion (in local frame) of SAM and the resuls are discussed

Detection of Diseases in Flora Through Leaf Image Classification by Convolution Neural Network

The quality of human existence and economic standing are significantly impacted by agriculture. It is the foundation of a nation's economic structure. Therefore, early diagnosis of plant diseases is crucial in both the agricultural sector and in people's daily life. Hunger and starvation are caused by agricultural losses due to plant diseases, especially in less developed nations where access to disease-controlling measures is limited and yearly losses of 30 to 50 percent for main crops are not unusual. Due to inadequate diagnosis of plant diseases, many plants die. Initially, diagnosis of plant disease was performed using MATLAB and machine learning algorithms including SVM. But these diagnoses did not provide accurate results. Also, in previous works website has not been created. To overcome this problem, a CNN model has been proposed that detects plant diseases. This CNN model has been deployed to the website. On this website, the image can be uploaded, and the disease gets predicted according to the image. The detected disease gets displayed on the website. To the CNN model, 15 cases have been fed, including both healthy and unhealthy leaves. The proposed model achieves a greater accuracy of more than 95%. This work offers a major benefit to the farmers by helping them in detecting plant diseases without requiring any special hardware or software

Enhancing Skin Cancer Diagnosis with Deep Learning-Based Classification

The diagnosis of skin cancer has been identified as a significant medical challenge in the 21st century due to its complexity, cost, and subjective interpretation. Early diagnosis is critical, especially in fatal cases like melanoma, as it affects the likelihood of successful treatment. Therefore, there is a need for automated methods in early diagnosis, especially with a diverse range of image samples with varying diagnoses. An automated system for dermatological disease recognition through image analysis has been proposed and compared to conventional medical personnel-based detection. This project proposes an automated technique for skin cancer classification using images from the International Skin Imaging Collaboration (ISIC) dataset, incorporating deep learning (DL) techniques that have demonstrated significant advancements in artificial intelligence (AI) research. An automated system that recognizes and classifies skin cancer through deep learning techniques could prove useful in the medical field, as it can accurately detect the presence of skin cancer at an early stage. The ISIC dataset, which includes a vast collection of images of various skin conditions, provides an excellent opportunity to develop and validate deep learning algorithms for skin cancer classification. The proposed technique could have a significant impact on the medical industry by reducing the workload of medical personnel while providing accurate and timely diagnoses.

ANTAGONISTIC POTENTIAL OF FLUORESCENT Pseudomonas AND ITS IMPACT ON GROWTH OF TOMATO CHALLENGED WITH PHTOPATHOGENS

This study focused on the antagonistic potential of fluorescent Pseudomonas in vitro, and its inoculation effect on growth performance of Lycopersicon esculentum in Fusarium oxysporum and Rhizoctonia solani infested soil. Biochemical characteristics of fluorescent Pseudomonas showed that all ten isolates were positive to catalase, amylase, gelatinase and siderophore production. While three isolates (Pf5, Pf6 and Pf9) were oxidase positive, nine isolates (Pf1, Pf2, Pf3, Pf4, Pf6, Pf7, Pf8, Pf9, and Pf10) were tolerant to 6.5% NaCl. Isolates Pf5 and Pf6 were resistant to all the test antibiotics; in contrast, the remaining eight isolates responded differently to different antibiotics. Isolates Pf5 and Pf6 were antagonistic against 14 bacterial species, and two pathogenic fungi (F. oxysporum and R. solani). Inoculation with fulorescent Pseudomonas Pf5 induced a significant increase in root and shoot length, and dry weight. Treatment of plants with either F. oxysporum or R. solani drastically reduced the root and shoot length and dry weight of the plant. However, in the presence of fluorescent Pseudomonas the adverse effect of the pathogens on growth of L. esculentum was alleviated.Cette \ue9tude a port\ue9 sur le potentiel antagonistique du Pseudomonas fluorescent, in vitro et les effets de son inoculation sur la performance en croissance du Lycopersicon esculentum dans le sol infest\ue9 par le Fusarium oxysporum et le Rhizoctonia solani . Les caract\ue9ristiques biochemiques du Pseudomonas fluorescent ont montr\ue9 que tous les dix isolats \ue9taient positives eu \ue9gard \ue0 la production de catalase, amylase, g\ue9latinase et sid\ue9rophore. Alors que trois isolats (Pf5, Pf6 and Pf9) \ue9taient oxidase positifs, neuf isolats (Pf1, Pf2, Pf3, Pf4, Pf6, Pf7, Pf8, Pf9, et Pf10) \ue9taient tolerant au 6.5% NaCl. Les isolats Pf5 et Pf6 \ue9taient r\ue9sistants \ue0 tous les test antibiotiques; au contraire, les huit isolats restants ont r\ue9pondu diff\ue9remment aux diff\ue9rents antibiotiques. Les isolats Pf5 et Pf6 \ue9taient antagonistiques contre 14 esp\ue8ces de bact\ue9ries, et deux champignons pathogeniques (F. oxysporum et R. solani). L\u2019inoculation avec Pseudomonas fulorescent Pf5 a induit une augmentation significative des raciness et de la longueur des tiges, ainsi que du poids sec. Le traitement de plants avec du F. oxysporum ou du R. solani ont radicalement r\ue9duit la longueur des raciness et tiges ainsi que le poids sec du plant. Cependant, en pr\ue9sence du Pseudomonas fluorescent, l\u2019effet adverse du pathog\ue8ne sur la croissance du L. esculentum \ue9tait allevi\ue9

Optimization of rootkit revealing system resources – A game theoretic approach

Malicious rootkit is a collection of programs designed with the intent of infecting and monitoring the victim computer without the user’s permission. After the victim has been compromised, the remote attacker can easily cause further damage. In order to infect, compromise and monitor, rootkits adopt Native Application Programming Interface (API) hooking technique. To reveal the hidden rootkits, current rootkit detection techniques check different data structures which hold reference to Native APIs. To verify these data structures, a large amount of system resources are required. This is because of the number of APIs in these data structures being quite large. Game theoretic approach is a useful mathematical tool to simulate network attacks. In this paper, a mathematical model is framed to optimize resource consumption using game-theory. To the best of our knowledge, this is the first work to be proposed for optimizing resource consumption while revealing rootkit presence using game theory. Non-cooperative game model is taken to discuss the problem. Analysis and simulation results show that our game theoretic model can effectively reduce the resource consumption by selectively monitoring the number of APIs in windows platform

Uniform accelerated motions

An Affine matrix which maps an initial and final pose can be computed by solving a system of linear equations. Then there exists an interesting problem of finding a time varying affinity which maps the given set of poses and if it exists is always unique and should hold some interesting properites such as affine-invariant, reversible, preserve rigidity, similarities and volume. The Steady Affine Motions and Morphs (SAM) introduced by Jarek Rossignac and Alvar Vinacua solved this problem of time varying affinity and defines the quality of such affinity by the term steadiness. Until SAM, no mathematical definition of steadiness was available and intuitively SAM defined a steady animation to be continuous, to vary dimensions and angles monotonically and rather uniformly, and to move points along pleasing arcs that are free of unnecessary kinks or loops. The authors defined the term ”Steady” as a constant velocity motion in the local moving frame. SAM creates pleasing in-betweening motions that interpolates between an initial and final pose, B and C and the derived equation of beauty was At B with A = C B·-1. SAM is affine-invariant, reversible, preserves isometries (i.e., rigidity), similarities and volume. Previously proposed approaches came up with a solution for the time varying affinity problem, but there was no proper definition of how beautiful or how good the motion was. With the advent of SAM, the beauty of a motion can now be measured by the unsteadiness and Steady Affine motions and morphs is the one solution which comes to have a value of zero for the unsteadiness term. Uniform Accelerated Motions (UAM) carries forward the above definition of steadiness into a constant acceleration motion in the local moving frame. The time varying affinity At is computed using closed form expressions and some of its interesting properties are studied. The constant acceleration motion (in local frame) in UAM is then compared with the constant velocity motion (in local frame) of SAM and the resuls are discussed

Genetic variability, heritability and genetic advance for yield and yield components in watermelon (Citrullus lanatus Thunb.)

Field investigation was carried out to study the genetic variability, heritability and genetic advance and the variability studies showed significant differences among the thirty genotypes for all the thirteen characters. Yield per plant was maximum in CL 4 genotype collected from Atchirupakkam in Villupuram district. The characters viz., number of vines per plant, sex ratio, days to first female flowers, node number of first female flower, days to fruit maturity and number of fruits per plant were recorded the maximum in the same genotype. Genetic analysis indicated maximum phenotypic and genotypic coefficient of variation for single fruit weight and 100 seed weight. The characters viz., fruits diameter, flesh thickness, number of fruits per plant and yield per plant, recorded highest estimate of PCV and moderate estimation of GCV. The characters viz., number of seeds per fruits, flesh thickness, number of primary branches and fruit diameter recorded moderate estimate of PCV and GCV. Lower estimation of GCV was observed for sex ratio, fruit length and number of male and female flowers. High heritability (broad sense) was observed for 100 seed weight, number of seeds per fruit, single fruit weight, vine length, fruit diameter, fruit length, flesh thickness, number of male flowers,sex ratio, yield per plant, number of primary branches per plant, number of female flowers and number of fruits per plant. Based on mean performance, CL 4 followed by CL 22 and CL 10 were selected as the best genotypes in watermelon for the costal ecosystem, by virtue of their higher yield combined with desirable component characters