International Journal of Advances in Applied Sciences
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A comparison of the carbon footprint of pavement infrastructure and associated materials in Indiana and Oklahoma
Get PDFAlthough often overlooked, infrastructure has a significant role in modern society. It is necessary means of transportation for goods and services needed to support commerce. It is this need and the need for continued economic development that causes the continuous infrastructure construction and its’ associated greenhouse gas emissions. Infrastructure construction requires energy to process raw materials, transport, mix and final construction. Greenhouse gas emissions from pavement sections have previously been identified for pavement preservation techniques. This research further evaluates greenhouse gas emissions for typical pavement sections from Indiana and Oklahoma to determine the carbon footprint based on linear foot of pavement. The comparison of CO2e of two typical roadway sections finds the difference in carbon footprint since variation in their minimum roadway. The carbon footprint of typical utility pipe with HDPE produces minimum CO2e and steel produces maximum CO2e. Soil base remediation options produce minimum CO2e and stabilized aggregate base produces maximum CO2e. Carbon offsets are determined by choosing vegetative options, soil remediation methods and appropriate pavement. This study is limited to a few pavement sections with a small variety of typical anticipated carbon offsets that would be seen in roadway construction. The index presented allows users to simply quantify benefits of the carbon offsets
Overview of soft intelligent computing technique for supercritical fluid extraction
Get PDFOptimization of Supercritical Fluid Extraction process with mathematical modeling is essential for industrial applications. The response surface methodology (RSM) has been proven to be a useful and effective statistical method for studying the relationships between measured responses and independent factors. Recently there are growing interest in applying smart system or artificial technique to model and simulate a chemical process and also to predict, compute, classify and optimize as well as for process control. This system works by generalizing the experimental result and the process behavior and finally predict and estimate the problem. This smart system is a major assistance in the development of process from laboratory to pilot or industrial. The main advantage of intelligent systems is that the predictions can be performed easily, fast, and accurate way, which physical models unable to do. This paper shares several works that have been utilizing intelligent systems for modeling and simulating the supercritical fluid extraction process
A study secure multi authentication based data classification model in cloud based system
Get PDFCloud computing is the most popular term among enterprises and news. The concepts come true because of fast internet bandwidth and advanced cooperation technology. Resources on the cloud can be accessed through internet without self built infrastructure. Cloud computing is effectively manage the security in the cloud applications. Data classification is a machine learning technique used to predict the class of the unclassified data. Data mining uses different tools to know the unknown, valid patterns and relationships in the dataset. These tools are mathematical algorithms, statistical models and Machine Learning (ML) algorithms. In this paper author uses improved Bayesian technique to classify the data and encrypt the sensitive data using hybrid stagnography. The encrypted and non encrypted sensitive data is sent to cloud environment and evaluate the parameters with different encryption algorithms
Development of software defect prediction system using artificial neural network
Get PDFSoftware testing is an activity to enable a system is bug free during execution process. The software bug prediction is one of the most encouraging exercises of the testing phase of the software improvement life cycle. In any case, in this paper, a framework was created to anticipate the modules that deformity inclined in order to be utilized to all the more likely organize software quality affirmation exertion. Genetic Algorithm was used to extract relevant features from the acquired datasets to eliminate the possibility of overfitting and the relevant features were classified to defective or otherwise modules using the Artificial Neural Network. The system was executed in MATLAB (R2018a) Runtime environment utilizing a statistical toolkit and the performance of the system was assessed dependent on the accuracy, precision, recall, and the f-score to check the effectiveness of the system. In the finish of the led explores, the outcome indicated that ECLIPSE JDT CORE, ECLIPSE PDE UI, EQUINOX FRAMEWORK and LUCENE has the accuracy, precision, recall and the f-score of 86.93, 53.49, 79.31 and 63.89% respectively, 83.28, 31.91, 45.45 and 37.50% respectively, 83.43, 57.69, 45.45 and 50.84% respectively and 91.30, 33.33, 50.00 and 40.00% respectively. This paper presents an improved software predictive system for the software defect detections
Trilateration based localization method using mobile anchor in wireless sensor networks
Get PDFLocalization in wireless sensor networks (WSNs) is essential in many applications like target tracking, military applications and environmental monitoring. Anchors which are equipped with global positioning system (GPS) facility are useful for finding the location information of nodes. These anchor nodes may be static or dynamic in nature. In this paper, we propose mobile anchors assisted localization algorithm based on regular hexagons in two-dimensional WSNs. We draw a conclusion that the number of anchor nodes greatly affect the performance of localization in a WSN. An optimal number of anchor nodes significantly reduces the localization error of unknown nodes and also guarantees that unknown nodes can obtain high localization accuracy. Because of the mobility of anchor nodes high volume of sensing region is covered with less period of time and hence the coverage ratio of the proposed algorithm increases. Number of communications also decreases for the reason that the system contains loge (n) number of anchor nodes which leads to less energy consumption at nodes. Simulation results show that our LUMAT algorithm significantly outperforms the localization method containing single anchor node in the network. Movement trajectories of mobile anchors should be designed dynamically or partially according to the observable environment or deployment situations to make full use of real-time information during localization. This is the future research issue in the area of mobile anchor assisted localization algorithm
Fault analysis in power system using power systems computer aided design
Get PDFThis work presents a fault analysis simulation model of an IEEE 30 bus system in a distribution network. This work annalysed the effect of fault current and fault voltage in a distribution system. A circuit breaker was introduced into the system to neutralize the effect of the fault. The system was run on a PSCAD software and results were obtained. The system was monitored based on the start time and the end time of the fault and how well the circuit breaker reacts with those times. Fault occurred from 0.100 to 0.300 seconds before it was removed. At the time fault was not applied (i.e. from 0.00 to 0.100 and from 0.300 to 0.72), the circuit breaker was close and became open when fault was applied so as to cut off current flow through the line.The result obtained gave the disruption caused by the fault and the quick response of the circuit breaker in neutralizing it. Results gotten are based on when the circuit breaker is close and no fault is applied and when the circuit breaker is open due to fault. From this work, it was obtained that circuit breakers are very essential in system protection and reliability
SU(3) Symmetry in hafnium isotopes with even neutron N=100-108
Get PDFIn this paper, we have reviewed the calculation of ground states energy level up to spin 14+, electric quadrupole moments up to spin 12+, and reduced transition probabilities of Hafnium isotopes with even neutron N = 100-108 by Interacting Boson Model (IBM-1). The calculated results are compared with previous available experimental data and found good agreement for all nuclei. Moreover, we have studied potential energy surface of those nuclei. The systematic studies of quadrupole moments, reduced transition strength, yrast level and potential energy surface of those nuclei show an important property that they are deformed and have dynamical symmetry SU(3) characters
Efficiency of bond graph and external model integration for alarm processing of a central air conditioning system
Get PDFThe design of a supervision system based on the external model by structuring the industrial process according to several modes of operation (degraded and normal). The disadvantage of this model is that it describes the industrial process components as functions regardless of their dynamics without going into detail. Hence the interest of the bond graph model to fill the external model limits. The performance of the proposed supervisory system using both models lies in the detection and location of faults for each mode of operation. The bond graph model enriched by the concept of causality and thanks to these structural properties can clearly display the elements of the physical system taking into account their dynamics in normal and abnormal operation. The results of our research have been applied to central air conditioning system; the development of the proposed project has proceeded from the modeling stage to the reconfiguration stage of the system
Design of frequency selective surface comprising of dipoles using artificial neural network
Get PDFThis paper depicts the design of Frequency Selective Surface (FSS) comprising of dipoles using Artificial Neural Network (ANN). It has been observed that with the change of the dimensions and periodicity of FSS, the resonating frequency of the FSS changes. This change in resonating frequency has been studied and investigated using simulation software. The simulated data were used to train the proposed ANN models. The trained ANN models are found to predict the FSS characteristics precisely with negligible error. Compared to traditional EM simulation softwares (like ANSOFT Designer), the proposed technique using ANN models is found to significantly reduce the FSS design complexity and computational time. The FSS simulations were made using ANSOFT Designer v2 software and the neural network was designed using MATLAB software
Enrich multi-channel P2P VoD streaming based on dynamic replication strategy
Get PDFPeer-to-Peer Video-on-Demand (VoD) is a favorable solution which compromises thousands of videos to millions of users with completeinteractive video watching stream. Most of the profitable P2P streaming groupsPPLive, PPStream and UUSee have announced a multi-channel P2P VoD system that approvals user to view extra one channel at a time. The present multiple channel P2P VoD system resonant a video at a low streaming rate due to the channel resource inequity and channel churn. In order to growth the streaming capacity, this paper highlights completely different effective helpers created resource balancing scheme that actively recognizes the supply-and-demand inequity in multiple channels. Moreover, peers in an extra channel help its unused bandwidth resources to peers in a shortage channel that minimizes the server bandwidth consumption. To provide a desired replication ratio for optimal caching, it develops a dynamic replication strategy that optimally tunes the number of replicas based on dynamic popularity in a distributed and dynamic routine. This work accurately forecasts the varying popularity over time using Auto-Regressive Integrated Moving Average (ARIMA) model, an effective time-series forecasting technique that supports dynamic environment. Experimental assessment displays that the offered dynamic replication strategy which should achieves high streaming capacity under reduced server workload when associated to existing replication algorithms