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- 저자 : Amitava Choudhury (검색결과 3 건)
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Pritam Mandal,Amitava Choudhury,Amitava Basu Mallick,Manojit Ghosh 대한금속·재료학회 2023 METALS AND MATERIALS International Vol.29 No.1
The purpose of this investigation is to predict the different phases present in various high entropy alloys and subsequentlyclassify their crystal structure by various machine learning algorithms using five thermodynamic, configurational andelectronic parameters, which are considered to be essential for the formation of high entropy alloy phases. Proper predictionof phases and crystal structures can eventually trace the properties of high entropy alloy, which is crucial for selectingthe suitable elements for designing. The model has been developed by various machine learning (ML) algorithms using anexperimental dataset consisting of 322 different HEAs, including 258 solid solution (SS), 31 intermetallic (IM), and 33 amorphous(AM) phases. The ML algorithms include (1) K-nearest neighbours (KNN), (2) support vector machines (SVM), and(3) logistic regression (LR), (4) decision tree (DT), (5) random Forest (RF), and (6) gaussian naive bayes classifier. Amongthem, both DT and SVM algorithms exhibited the highest accuracy of 93.84% for phase prediction. Crystal structure classificationof SS phases was also done using a dataset consisting of 194 different HEAs data, including 76 body centered cubic(BCC), 61 face centered cubic (FCC) and 57 mixed body-centered and face-centered cubic (BCC + FCC) crystal structuresand found that the SVM algorithm shows the highest accuracy of 84.32%. The effect of the parameters on determining theaccuracy of the model was calculated and tracking the role of individual parameters in phase construction was also attempted.
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CGI based syslog management system for virtual machines
Kamal Dua,Tanupriya Choudhury,Uppara Rajanikanth,Amitava Choudhury 대한공간정보학회 2020 Spatial Information Research Vol.28 No.4
Undoubtedly, logs are brain of any software system. Development, debugging and upgradation of software applications became much easier due to the logging or auditing concept in computer science field. Virtual Machines also log and timestamp every activity that take place during their runtime. Gathering system details from those lengthy log files is a hectic work for the end-user since single log file contains millennial entries of audited log data. A management system can be very helpful solution and required for the analytical scanning and the visualization of the logged data and thus providing the way to end user for the relevant information about the virtual machines running on the hypervisors. The same system can help developers to gather relevant log entries and presenting data collectively to the end user. This system not only helps in providing and presenting details but also act as an alert system to notify user fatal errors occurred during runtime. Statistical usage information or notification system can further be developed by the means of this syslog system. This paper will present how developers can build an efficient Syslog Management System on the web using the (CGI) Common Gateway Interface in the C programming language and also mentions how CGI environment can be achieved in the Apache Tomcat webserver to build dynamic web tools. Also, it provides basic idea how C can be used effectively in the CGI interface to provide better methods for obtaining and extracting relevant system data.
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Incorporating Smart Software-defined Networks to Enhance Resilience and Survivability in the Cloud
Indushree Banerjee,Indika Perera,Amitava Nag,Joydeep Choudhury 한국산학기술학회 2015 SmartCR Vol.5 No.4
With increased dependence on grids and the cloud, resilience and survivability become pre-requisites of backbone network infrastructure. Due to the unprecedented migration of data centers to both public and private cloud services; the need of an environment that provides agility combined with security and scalability becomes mandatory. The changing network scenario requires a standardized separation of data and control planes that will allow transparency and increase network resilience as metrics to improve security. Software-defined networks are being considered by many vendors to provide the ultimate solution to meet the increasing demands and serve the elastic growth of cloud services while providing sufficient flow monitoring, fault detection, and network management properties in highly-complex backbone infrastructure networks.
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