Global Journal of Computer Science and Technology (GJCST)
Not a member yet
1830 research outputs found
Sort by
Historical College Scorecard Big Data Analysis using In-Memory Processing
Get PDFData set is collected for colleges of United States. We would like to analyze different dimensions like SAT scores, ear- ning after graduation, net price and grant financial aids which is a great analyzation for the students. Big Data platform and BI tool such as Spark and tableau are adopted for data analy- zation and visualization. It is found that the top colleges for mean earnings are from medical field, mean earnings with respect to states, detailed comparison of average net price of California and New York, SAT scores for different colleges and also average undergraduates receiving Pell Grant in each colle- ges which will help students to select a college which meets their requirement
Concept Drift Detection in Data Stream Mining: The Review of Contemporary Literature
Get PDFMining process such as classification, clustering of progressive or dynamic data is a critical objective of the information retrieval and knowledge discovery; in particular, it is more sensitive in data stream mining models due to the possibility of significant change in the type and dimensionality of the data over a period. The influence of these changes over the mining process termed as concept drift. The concept drift that depict often in streaming data causes unbalanced performance of the mining models adapted. Hence, it is obvious to boost the mining models to predict and analyse the concept drift to achieve the performance at par best. The contemporary literature evinced significant contributions to handle the concept drift, which fall in to supervised, unsupervised learning, and statistical assessment approaches. This manuscript contributes the detailed review of the contemporary concept-drift detection models depicted in recent literature. The contribution of the manuscript includes the nomenclature of the concept drift models and their impact of imbalanced data tuples
Node.js Challenges in Implementation
Get PDFNode.js gave rise to the Full Stack Developers who are now able to manage server and client side by their own. Node.js is fast and reliable for heavy files and heavy network load applications due to its event driven, non-blocking, and asynchronous approaches, where developers can also maintain a complete projects in single pages (SPA) and can use for IOT. The result of study concludes from a survey and from literature review the implementation areas and challenges of the Node.js. Lastly will provide suggestion on how to improve to overcome the challenges
An Efficiency Study on Fault Tolerent Fir Filters
Get PDFIn this Digital World, Digital filters are the boom for modern digital communications in which Fir filters play a vital role. But the reliability of these filters is still a paradox. Nowadays electronic devices with multiple numbers of filters are used in various fields. Hence the performance and reliability of the filters must be improved. A number of techniques have been introduced to detect and correct errors that occur in those filter circuits. In this paper, the use of hamming code error correction technique on 4 tap fir filters are studied in order to obtain optimized and efficient reliability
Potential of Big Data Analytics in Bio-medical and Health Care Arena: An Exploratory Study
No full textWith the leveraging emerging big Data in every industry Big Data can amalgamate all data related to patient to get a complete view of patient to analyze and predict the outcomes Using big data analytics as tools It can enhance development in new drugs health care financing process and clinical approaches and extends a lots of benefits such as better health care quality and efficiency fraud detection and early disease detection by means of analytics of big data This paper provides a general survey of current progress and advances in research arena of big data bio-medical and health care and some major challenges of big data concept and characteristics this concerns includes big data from bio-medical and health care arena benefits of big data its applications and opportunities Methods and technology progress about big data in bio-medical and health care and challenges of big data in both bio-medical and healthcare are also discusse
Quantum Computing Tutorial Bits vs Qubits and Shors Algorithm
Get PDFThe speculative inquiry that computation could be done in general more efficiently by utilizing quantum effects was introduced by Richard Feynman Peter Shor described a polynomial time quantum algorithm for factoring integers by a quantum machine which proved the speculation true Quantum systems utilize exponential parallelism which cannot be done by classical computers However quantum decoherence poses a difficulty for measuring quantum states in modern quantum computers This paper elaborates on some basic concepts applied to quantum computing It first outlines these key concepts introduces the mathematics needed for understanding quantum computing and finally explores the Shor s Algorithm as it applies to both classical and quantum computer securit
Web usage Mining: Web user Session Construction using Map-Reduce
Get PDFWeb Usage Mining deals with the understanding of user behavior while interacting with the website by using various log files The whole process of Web Usage Mining gets completed in three phases namely Data Preprocessing Pattern Discovery and Pattern Analysis Data Preprocessing is important because it takes 80 of the time of the whole process of Web Usage Mining Data Preprocessing involves Data Cleaning User Identification and Session Identification In Session Identification we find out the set of pages visited by a user within the duration of one particular visit to a website also called as Sessionization In paper 1 we proposed a new method for session construction As the size of log files are very large so there is a requirement of an approach for Session Identification by which processing time of our proposed method will be reduced to a great extent In this paper we used Map-reduce method to calculate sessions in which we combine both time and user navigation method This approach is faster than the existing approach because we have performed the whole process in distributed environmen
Internet Traffic Flow Analysis using Hadoop
Get PDFThe internet traffic analysis elucidates the network administrator for monitoring the ongoing operation in the network and to understand the network so that the behavior could be examined and large problem can be examined. Flow analysis assists in traffic management, allocation of resources and fault tolerance. Due to the fast increase in internet user simultaneously the network usage has also escalated rapidly. The major problem of this fast growth in network is the traffic management, storing of traffic data and analysis this enormous amount of data in a single machine. To resolve this issue hadoop has been implemented to scan multiple input data and produce output for traffic identification and clustering flow. In this paper internet traffic flow analysis has been done using hadoop. In this proposed method system accepts packet data as input from network and this input is appended to hadoop distributed file system (HDFS) and at last processing is done through MapReduce. Once the output has been generated the network administrator analyses the internet traffic and troubleshoot any problem if necessary
Study of Effective Scheduling Algorithm for Application of Big Data
Get PDFIn this new era with the advancement in the technological world the data storage, analysis becomes a major problem. Although the availability of different data storage component like electronic storage such as hard drive or virtual storage such as cloud still the problems remains. The major issue is processing the data because usually the data is in several format and size. Usually processing such huge amount of data with several formats can be time consuming. Using of application such as Hadoop can be beneficial but using of scheduling algorithm can be the best way to for data set analysis to make the process time efficient and analysis the requirement of different scheduling algorithm for the specific data set. In this paper we analysis different data set to explain the most effective scheduling algorithm for that specific data set and then store and execute data set after processing