Artificial Intelligence

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I take the privilege to present the print version for the Volume 1 Issue (1) of Journal of Artificial

Intelligence Research & Advances. The intension of JoAIRA is to create an atmosphere that

stimulates creativeness, research and growth in the area of Artificial Intelligence.

The development and growth of the mankind is the consequence of brilliant Research done by

eminent Scientists and Engineers in every field. JoAIRA provides an outlet for Research findings

and reviews in areas of Artificial Intelligence found to be relevant for National and International

recent developments & research initiative.

The aim and scope of the Journal is to provide an academic medium and an important reference for

the advancement and dissemination of Research results that support high level learning, teaching and

research in the domain of Artificial Intelligence.

Finally, I express my sincere gratitude and thanks to our Editorial/ Reviewer board and Authors for

their continued support and invaluable contributions and suggestions in the form of authoring write

ups/ reviewing and providing constructive comments for the advancement of the journals. With

regards to their due continuous support and co-operation, we have been able to publish quality

Research/Reviews findings for our customers base.

I hope you will enjoy reading this issue and we welcome your feedback on any aspect of the Journal.

Dr. Archana Mehrotra

Director

STM Journals

Director's Desk

STM JOURNALS

1. AIS-MACA- Z: MACA based Clonal Classifier for Splicing Site, Protein Coding and Promoter Region Identification in Eukaryotes

Pokkuluri Kiran Sree, Inampudi Ramesh Babu , SSSN Usha Devi N 1

2. An Implementation of Hospital Management System for Casualty based on Artificial Intelligence Abhishek Kumar, Rasika Giri, Namita Jathe, Ajinkya Marudwar, A. N Banubakode 7

3. Development of Smart Kitchen System using RFIDNikhil Jagtap, Seema Kedar, Akash Udhanshiv 12

4. Messenger RNA Approach for Identifying Inter-nucleotide Signals using Genomic SequencesPulugurta Krishna Subba Rao, M.S.N. Murthy 16

ContentsJournal of Artificial Intelligence Research & Advances

JoAIRA (2014) 1-6 © STM Journals 2014. All Rights Reserved Page 1

Journal of Artificial Intelligence Research & Advances

Volume 1, Issue 1

www.stmjournals.com

AIS-MACA- Z: MACA based Clonal Classifier for

Splicing Site, Protein Coding and Promoter Region

Identification in Eukaryotes

Pokkuluri Kiran Sree1*, Inampudi Ramesh Babu

2 ,

SSSN Usha Devi N

3

1Department of CSE, JNTU Hyderabad, India

2Department of CSE, ANU, Guntur, India

3Department of CSE, University College of Engineering, JNTUK, India

Abstract Bioinformatics incorporates information regarding biological data storage, accessing

mechanisms and presentation of characteristics within this data. Most of the problems in bioinformatics and be addressed efficiently by computer techniques. This paper aims at

building a classifier based on Multiple Attractor Cellular Automata (MACA) which uses

fuzzy logic with version Z to predict splicing site, protein coding and promoter region identification in eukaryotes. It is strengthened with an artificial immune system technique

(AIS), Clonal algorithm for choosing rules of best fitness. The proposed classifier can handle DNA sequences of lengths 54,108,162,252,354. This classifier gives the exact

boundaries of both protein and promoter regions with an average accuracy of 90.6%.

This classifier can predict the splicing site with 97% accuracy. This classifier was tested with 1, 97,000 data components which were taken from Fickett & Toung , EPDnew, and

other sequences from a renowned medical university.

Keywords: MACA(Multiple Attractor Cellular Automata), CA(Cellular Automata),

AIS (Artificial Immune System), Clonal Algorithm, AIS-MACA-Z(Artificial Immune

System- Multiple Attractor Cellular Automata-Version Z)

JoAIRA (2014) © STM Journals 2014. All Rights Reserved

Journal of Artificial Intelligence Research & Advances

Volume 1, Issue 1

www.stmjournals.com

An Implementation of Hospital Management System for

Casualty based on Artificial Intelligence

Abhishek Kumar*, Rasika Giri, Namita Jathe, Ajinkya Marudwar, A. N Banubakode Department of Information Technology JSPM’s RSCOE, Pune, Maharashtra, India

Abstract This paper proposes Hospital Management System for Casualty Based on AI. Artificial

Intelligence based casualty system provides decision making functionality without human

intervention. These days thousands of people die as they do not get medical care within critical time. To get medical facility to the patient on time we have designed this system.

Our system uses ANN Algorithm and kohonen’s Algorithm which uses neural network

theory for proper decision making and for providing the alerts simultaneously to doctors, ambulance, blood bank, police station and others, for providing medical facilities based

on type of casualty in time critical instant.

Keywords: Casualty Management, WAP Gateway, General Packet Radio Service

(GPRS), Artificial Intelligence, Kohonen’s Network.

JoAIRA (2014)© STM Journals 2014. All Rights Reserved

Journal of Artificial Intelligence Research & Advances

Volume 1, Issue 1

www.stmjournals.com

Development of Smart Kitchen System using RFID

Nikhil Jagtap*, Seema Kedar, Akash Udhanshiv JSPM’s RSCOE, UOP, Pune, Maharashtra, India

Abstract We've been implementing an application to keep track of the food inventory i.e. observing

the status of the inventory, creation of shopping list automatically without any human interaction based on the food status in the inventory and observing the level of food

containers to give an alert message to the user at times when food level is critical. Giving

an automation to all these daily routine tasks will reduce human efforts. Proposed system

will track the level of food items and based on it the system will create the shopping list

and the list will have the only food products at the critical level. Proposed system helps

users easily manage kitchen and daily needed food products. Smart Kitchen system using RFID (Radio Frequency Identification) helps in minimizing work load caused in today’s

traditional kitchen system. Every Food Product is identified by unique identification number which is being embedded in RFID tag. The old and traditional process of

working is being totally replaced by atomizing kitchen system. Proposed system is quite

efficient and time and cost of people can be saved. Android is currently all over the market because of its open source nature and almost everyone has an android device.

Thus, this paper discusses a mobile application using android which can efficiently

handle and manage the kitchen system work.

Keywords: Android, Radio Frequency Identification, RFID, RFID tag

JoAIRA (2014)© STM Journals 2014. All Rights Reserved

Journal of Artificial Intelligence Research & Advances

Volume 1, Issue 1

www.stmjournals.com

Messenger RNA Approach for Identifying

Inter-nucleotide Signals using Genomic Sequences

Pulugurta Krishna Subba Rao*1, M.S.N. Murthy

2

1Professor, Department of CSE, G.V.P College of Engineering, Madhurawada, Visakhapatnam

2Assistant Professor, Department of CSE, G.V.P College of Engineering,

Madhurawada, Visakhapatnam

Abstract The inter-nucleotide signals are a novel way of genomic signal representation of genomic data which is seen to have a discriminatory capability in highlighting the promoter region

of gene sequences. The results of applying DFT to in genomic sequence signals that they can discriminate using messenger RNA for identifying inter nucleotide sequences.

Genomic Signal Processing (GSP) applications in bioinformatics research have received

great attention in recent years, where new effective methods for genomic sequence analysis, such as the detection of converting the genomic sequences into signals have

been developed. The use of GSP principles to analyze genomic sequences that requires

defining an adequate representation of the nucleotide by numerical values, converting the nucleotide sequences into nucleotide signals. In this paper we present an approach of

GSP algorithm which is used in conversion of genomic sequences into signals and also calculating the peaks at coding regions this article also shows the comparative study at

the different peaks at a certain elapsed time. The position of these peaks helps in

identifying the motifs and the functional behavior of a gene for identifying the Bio Marker selection using a discrete Fourier transform approach

Keywords: Genomic signal processing, standard genomic sequences method, binary

standard selection method, nucleotide sequences, biomarker selection