1,301 research outputs found

    Estimation of the growth curve parameters in Macrobrachium rosenbergii

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    Growth is one of the most important characteristics of cultured species. The objective of this study was to determine the fitness of linear, log linear, polynomial, exponential and Logistic functions to the growth curves of Macrobrachium rosenbergii obtained by using weekly records of live weight, total length, head length, claw length, and last segment length from 20 to 192 days of age. The models were evaluated according to the coefficient of determination (R2), and error sum off square (ESS) and helps in formulating breeders in selective breeding programs. Twenty full-sib families consisting 400 PLs each were stocked in 20 different hapas and reared till 8 weeks after which a total of 1200 animals were transferred to earthen ponds and reared up to 192 days. The R2 values of the models ranged from 56 – 96 in case of overall body weight with logistic model being the highest. The R2 value for total length ranged from 62 to 90 with logistic model being the highest. In case of head length, the R2 value ranged between 55 and 95 with logistic model being the highest. The R2 value for claw length ranged from 44 to 94 with logistic model being the highest. For last segment length, R2 value ranged from 55 – 80 with polynomial model being the highest. However, the log linear model registered low ESS value followed by linear model for overall body weight while exponential model showed low ESS value followed by log linear model in case of head length. For total length the low ESS value was given by log linear model followed by logistic model and for claw length exponential model showed low ESS value followed by log linear model. In case of last segment length, linear model showed lowest ESS value followed by log linear model. Since, the model that shows highest R2 value with low ESS value is generally considered as the best fit model. Among the five models tested, logistic model, log linear model and linear models were found to be the best models for overall body weight, total length and head length respectively. For claw length and last segment length, log linear model was found to be the best model. These models can be used to predict growth rates in M. rosenbergii. However, further studies need to be conducted with more growth traits taken into consideratio

    The Spectrum of CoCl in the Photographic Infrared and the Visible

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    Experimental studies in Ultrasonic Pulse Velocity of roller compacted concrete pavement containing fly ash and M-sand

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    AbstractThis paper presents the experimental investigation results of Ultrasonic Pulse Velocity (UPV) tests conducted on roller compacted concrete pavement (RCCP) material containing Class F fly ash of as mineral admixture. River sand, M-sand and combination of M-sand and River sand are used as fine aggregate in this experimental work. Three types of fly ash roller compacted concrete mixes are prepared using above three types of fine aggregates and they are designated as Series A (River sand), Series B (manufactured sand) and Series C (combination of River sand and M-sand). In each series the fly ash content in place of cement is varied from 0% to 60%. In each series and for different ages of curing (i.e 3, 7, 28 and 90days) forty two cube specimens are cast and tested for compressive strength and UPV. The UPV results of fly ash containing roller compacted concrete pavement (FRCCP) show lower values at all ages from 3days to 90days in comparison with control mix concrete (0% fly ash) in all mixes. However, it is also observed that Series B and C mixes containing fly ash show better results in UPV values, compressive strength and Dynamic Elastic Modulus in comparison to Series A mixes with fly ash. Relationships between compressive strength of FRCCP and UPV and Dynamic Elastic Modulus are proposed for all series mixes. A new empirical equation is proposed to determine the Dynamic Elastic Modulus of FRCCP

    A Novel Approach for Detection of DoS / DDoS Attack in Network Environment using Ensemble Machine Learning Model

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    One of the most  serious threat to network security is Denial of service (DOS) attacks. Internet and computer networks are now important parts of our businesses and daily lives. Malicious actions have become more common as our reliance on computers and communication networks has grown. Network threats are a big problem in the way people communicate today. To make sure that the networks work well and that users' information is safe, the network data must be watched and analysed to find malicious activities and attacks. Flooding may be the simplest DDoS assault. Computer networks and services are vulnerable to DoS and DDoS attacks. These assaults flood target systems with malicious traffic, making them unreachable to genuine users. The work aims to enhance the resilience of network infrastructures against these attacks and ensure uninterrupted service delivery. This research develops and evaluates enhanced DoS/DDoS detection methods. DoS attacks usually stop or slow down legal computer or network use. Denial-of-service (DoS) attacks prevent genuine users from accessing and using information systems and resources. The OSI model's layers make up the computer network. Different types of DDoS strikes target different layers. The Network Layer can be broken by using ICMP Floods or Smurf Attacks. The Transport layer can be attacked using UDP Floods, TCP Connection Exhaustion, and SYN Floods. HTTP-encrypted attacks can be used to get through to the application layer. DoS/DDoS attacks are malicious attacks. Protect network data from harm. Computer network services are increasingly threatened by DoS/DDoS attacks. Machine learning may detect prior DoS/DDoS attacks. DoS/DDoS attacks proliferate online and via social media. Network security is IT's top priority. DoS and DDoS assaults include ICMP, UDP, and the more prevalent TCP flood attacks. These strikes must be identified and stopped immediately. In this work, a stacking ensemble method is suggested for detecting DoS/DDoS attacks so that our networked data doesn't get any worse. This paper used a method called "Ensemble of classifiers," in which each class uses a different way to learn. In proposed  methodology Experiment#1 , I used the Home Wifi Network Traffic Collected and generated own Dataset named it as MywifiNetwork.csv, whereas in proposed methodology Experiment#2, I used the kaggle repository “NSL-KDD benchmark dataset” to perform experiments in order to find detection accuracy of dos attack detection using python language in jupyter notebook. The system detects attack-type or legitimate-type of network traffic during detection ML classification methods are used to compare how well the suggested system works. The results show that when the ensembled stacking learning model is used, 99% of the time it is able to find the problem. In proposed methodology two Experiments are implemented for comparing detection accuracy with the existing techniques. Compared to other measuring methods, we get a big step forward in finding attacks. So, our model gives a lot of faith in securing these networks. This paper will analyse the behaviour of network traffics

    Synthesis based on cyclohexadienes. Part 22. Formal syntheses of patchouli alcohol and norpatchoulenol

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    The preparation of 6-endo-formyl-1,3,3-trimethylbicyclo[2.2.2]octan-2-one 7 and 6-endo-acetyl-1,3,3-trimethylbicyclo[2.2.2]octan-2-one 8, the two key intermediates for the synthesis of patchouli alcohol 1 and norpatchoulenol 2, is reported by a simple and short method from 2-methylbenzoic acid

    Development of a Modular Unit of a Higher Level Framework or Tool for Basic Programming Course Teaching Through E-Learning Mode

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    This paper reports about the development of a modular unit of a higher level framework or tool whose intended objective is the creation of animated lessons for basic programming (CS1) course in computer science discipline with visual aids. The goal of such lessons is to address the difficulties faced by the novice programmers in CS1 course.This module here after referred to as ‘type writer’allows instructors to render programmes or code snippets in a live typing manner as opposed to their sudden or en-block placement on the presentation area like a Power Point Slide; a commonly used approach in the present day eLearning.This project is planned to be executed in two stages and ‘type writer’ is the outcome of the first stage. This would be combined with another two modules that are planned to be developed in the second stage, to make the complete tool. The entire tool would be developed in Action Script 3.0 language that works on Adobe Flash Platform

    Studies on the Performance of Air Cyclone Separator for Removal of Particulate Matter

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    Emissions from industries and air pollution from these emissions adversely affects the environment and public health. For instance, India depends largely on coal for its power generation. The problem with Indian coal is that it carries a lot of dust with it. Hence, dust carried along with the flue gases has to be separated before sending the gases for further treatment. Cyclone separa-tor, bag filter and electrostatic precipitator have found applications in technological use. ESP demands high voltage (power requirements) whereas general bag filters cannot work beyond 120C. However, cyclone separators have less temperature and pressure limitations and requires low pressure drop. Hence, cyclone separators are usually selected to separate dust from fluid streams

    Some flow features of the Indian summer monsoon deduced from Nimbus-II radiation data

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    Radiation data obtained from Nimbus-II MRIR (10-11μ) and HRIR (3.5-4.1μ) radiometer for 14-19 June 1966, over the Indian Ocean are used to study some features of the monsoon circulation during the six-day period. Low values of radiation which are associated with cloudiness show two distinct features from 15-17 June: (i) a very extensive band of approximately 1000 km in width at the equator between 50°-60° E extending towards both hemispheres, and (ii) a synoptic-scale cell covering the equatorial region approx. between 70°-90° E and 0°-10° S. The two cloud systems are separated from each other by a wide region of high radiation indicating clear conditions. Sub-synoptic scale features could be detected in the radiation field (which in turn are related to the cloud field). Northern and Western sections of the Arabian Sea were relatively cloud-free. An attempt is made to relate the cloud fields with computed vertical motion fields. Areas of upward motion seem to coincide well with centers of low radiation (clouds) and those of subsidence with regions of high radiation. Horizontal flow features related to the computed vertical motion fields are discussed in the paper
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