International Journal of Advanced Studies in Computer Science and Engineering (IJASCSE)

                                                                                                                                                                                                   ISSN : 2278 7917 

Call For Papers

May 2019

  Submission         May 10

  Acceptance         May 20

  Publication          May 31

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International Journal of advanced studies in Computer Science and Engineering (IJASCSE) is here to provide a timely and broad coverage of research in ever-challenging field of Computer Science and Computer Science Engineering. IJASCSE is an interdisciplinary, peer reviewed, fully refereed, monthly, Open Access journal for research scholars with a mix of regular and theme based issues to share their new and advanced research in Computer Science and Engineering. 

The papers published at IJASCSE are currently Abstracted & Indexed by some world famous databases.

 Call For Papers

April  2019

     Submission                     April 10

      Notification                     April 20

      Publication                     April 30

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Open Access Database

IJASCSE is an online peer reviewed quality publication, which publishes research papers from diverse fields in computers, sciences, engineering and technologies that emphasizes new research, development and their applications. It provides an open access database for all who are interested to exchange their research work, technical notes & surveying results among professionals through out the world.


 IJASCSE volume 5 issue 7 (Theme: Communications, Internet and Information Technology)                            

A Systematic Review of Scheduling in Cloud Computing Framework

Abhikirti Narwal, Sunita Dhingra

AbstractThe approach of cloud computing is a model of administration in circulated frameworks. It urges analysts to examine its advantages and disadvantages in executing applications for example work processes. The up coming era of cloud computing will find out how adequately the framework are instantiated and accessible. It will also tell how the assets are used progressively. Cloud computing term is used to portray an another group of system based on registering applications over the web. The essential advantage of using Clouds is its application versatility. It is an exceptionally advantageous for the application which is sharing their assets on various hubs. Scheduling the assignment is truly an experimenting activity in cloud environment. Normally errands are scheduled by client prerequisites. New scheduling systems should be proposed to beat the issues proposed by system properties in the middle of client and assets. The New scheduling methodologies might utilize a portion of the traditional scheduling ideas to join them together with a few system aware techniques to give solutions for better and more effective task scheduling. This paper gives the study on various scheduling calculations that systematize the scheduling issue in cloud computing, and present a cloud scheduling pecking order.


Ahmed Nasraden Milad, M. Aziz M, Rahamadwati

Abstract Artificial neural network (ANN) is one of the most advanced technology fields, which allows machines to learn from examples in a manner similar to the human brain learning. ANNs applied to many scientific fields such as function approximation, data processing, classification, signal processing and much more. The main problem in communication field is the effect of noise into the signal. In this paper an artificial neural network demodulator (ANND) to demodulate quadrature amplitude modulating signal (QAM) is proposed. This project attempts to develop communication systems by developing neural networks and machine learning. This paper will help giving contribution to reduce the bit error rate (BER), optimize the quality of received data, reducing the effect of noise on data communications, optimization of the signal demodulator quality, increasing the quality of communication systems, speed up the process of neural network demodulator, developing the signal recovery and demodulating techniques. The artificial neural network, random data, noise, QAM modulator and demodulator are all simulated by GNU Octave software on this paper



Vishnu Sharma, Vijay Singh Rathore

Abstract - The focus of this paper is to suggest a method which enhance the adaptability of available components. This paper suggests an architecture which involves traditional (Keywords based) and advanced techniques to search a component. If still suitable component is not found then and few changes in the architecture of component are required, a user may suggest the changes. This response is sent to server. Server lets this response to be implemented based on some properties of the available component. Improved component is verified with available models. If it passes this verification step. A new qualified component is made available to user to download. It can be downloaded and implemented in user projects.

Structural Feature and Named Entity Extraction Using Enhanced-CRF and Gazetteer

Lokesh Sharma, Namita Mittal

Abstract - Question Answering (QA) research is an important and challenging task in Natural Language Processing. QA aims to extract an exact answer. The motivation behind QA research is the requirement of the user who is using state-of-the-art search engines. Rather than a list of documents that probably contain the answer the user expect an exact answer. Furthermore, the named entities are the basic building blocks of text irrespective of the language. Named Entity Recognition (NER) system classifies named entities from the considered text to predefined categories like person name, location, organization etc. Many approaches based on transliteration, Hidden Markov Model, maximum entropy model have been developed so far. In QA, we have used Conditional Random Fields model with added language dependent features to extract named entities; along with CRF model based tagging we have proposed a gazetteer to match specific entities. 

Keywords – Cloud Computing, Job Scheduling, Efficiency, Performance, Cost, Resource allocation

Keywords—demodulation, ANN, communication, QAM, BER, GNU octave simulation

Keywordscomponent; formatting; style; styling; insert (key words), MVC(Model View Controller), SQL(Structured Query Language), Technomics Compiler, IA(Interface Automata),reuse, Component Retrieval Technique (CRT)

Keywords - semantic features, structural feature, lexical features, named entity, question answering Structural Feature and Named Entity Extraction Using Enhanced-CRF and Gazetteer

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