Soft Computing, Artificial Intelligence and Applications

Bacteria Identification From Microscopic Morphology: A Survey Noor Amaleena Mohamad, Noorain Awang Jusoh, Zaw Zaw Htike and Shoon Lei Win International Islamic University Malaysia, Malaysia ABSTRACT Great knowledge and experience on microbiology are required for accurate bacteria identification.Automation of bacteria identification is required because there might be a shortage of skilled microbiologists and clinicians at a time of great need. There have been several attempts to perform automatic background identification. This paper reviews state-of-the-art automatic bacteria identification techniques. This paper also provides discussion on limitations of state-of-the-art automatic bacteria identification systems and recommends future direction of automatic bacteria identification. KEYWORDS Bacteria Identification, Cocci,Bacilli, Vibrio, Naïve Bayes, Machine Learning Original Source URL: http://airccse.org/journal/ijscai/papers/3214ijscai01.pdf http://airccse.org/journal/ijsc...

Cancer Prognosis Prediction Using Balanced Stratified Sampling J.S.Saleema1, N.Bhagawathi2, S.Monica2, P.Deepa Shenoy2, K.R.Venugopal2 and L.M.Patnaik3, 1Christ University, India 2University Visvesvaraya College of Engineering, India 3Indian Institute of Science, India ABSTRACT High accuracy in cancer prediction is important to improve the quality of the treatment and to improve the rate of survivability of patients. As the data volume is increasing rapidly in the healthcare research, the analytical challenge exists in double. The use of effective sampling technique in classification algorithms always yields good prediction accuracy. The SEER public use cancer database provides various prominent class labels for prognosis prediction. The main objective of this paper is to find the effect of sampling techniques in classifying the prognosis variable and propose an ideal sampling method based on the outcome of the experimentation. In the first phase of this work the traditional rando...

Artificial Intelligence Handling Through Teaching and Learning Process and It’s Effect on Science-Based Economy Mohammad Ziaaddini and Aref Tahmasb shahidBahonar University, Iran ABSTRACT According to this fact that educational system is the base of constant development in every country and this system educates human-forces and this forces,are accelerators and a factor, of achieving the goals of development,the educational system can play, Major role in the context economic behavior, in this context some concepts are regarded as behavioral targets and performance.In educational system, handling artificial intelligence, in teaching and learning process, had a surprising evolution through educational advantages, making job, respecting customers rights and customer relationship management, to assist priority and citizenship, correct investment through formal markets. Science-Based economy, resistible economy and a positive view to job and Iran capital,including concepts which can be i...

Temporally Extended Actions For Reinforcement Learning Based Schedulers Prakhar Ojha, Siddhartha R Thota, Vani M and Mohit P Tahilianni National Institute of Technology Karnataka, India ABSTRACT Temporally extended actions have been proved to enhance the performance of reinforcement learning agents. The broader framework of ‘Options’ gives us a flexible way of representing such extended course of action in Markov decision processes. In this work we try to adapt options framework to model an operating system scheduler, which is expected not to allow processor stay idle if there is any process ready or waiting for its execution. A process is allowed to utilize CPU resources for a fixed quantum of time (timeslice) and subsequent context switch leads to considerable overhead. In this work we try to utilize the historical performances of a scheduler and try to reduce the number of redundant context switches. We propose a machine-learning module, based on temporally extended reinforcemen...

Knowledgebase Systems in Neuro Science - A Study D.K.Sreekantha1, T.M.Girish2 and R.V.Kulkarni3 1Nitte Mahalinga Adyanthaya Memorial Institute of Technology, India 2Basaveshwar Science College, India 3Chhatrapati Shahu Institute of Business Education and Research, India ABSTRACT The improvement of health and nutritional status of the society has been one of the thrust areas for social developments programmes of the country. The present states of healthcare facilities in India are inadequate when compared to international standards. The average Indian spending on healthcare is much below the global average spending. Indian healthcare Industry is growing at the rapid pace of more than 18%, the fastest in the world. The prospects for Indian healthcare are to the tune of USD 40 billion, while global market is USD 1660 trillion. India has all the prospects to become medical tourism destination of the world, because it has a large pool of low-cost scientifically trained technical person...

An Iranian Cash Recognition Assistance System For Visually Impaireds Esmaiel Nojavani, Azade Rezaeezade and Amirhassan Monadjemi University of Isfahan, Iran ABSTRACT In economical societies of today, using cash is an inseparable aspect of human’s life. People use cash for marketing, services, entertainments, bank operations and so on. This huge amount of contact with cash and the necessity of knowing the monetary value of it caused one of the most challenging problems for visually impaired people. In this paper we propose a mobile phone based approach to identify monetary value of a picture taken from a banknote using some image processing and machine vision techniques. While the developed approach is very fast, it can recognize the value of the banknote by an average accuracy rate of about 97% and can overcome different challenges like rotation, scaling, collision, illumination changes, perspective, and some others. KEYWORDS Cash Identification Using Mobile, Visually Impaired As...

An Experimental Study of Feature Extraction Techniques in Opinion Mining J. Ashok Kumar and S. Abirami Anna University, India ABSTRACT The feature selection or extraction is the most important task in Opinion mining and Sentimental Analysis (OSMA) for calculating the polarity score. These scores are used to determine the positive, negative, and neutral polarity about the product, user reviews, user comments, and etc., in social media for the purpose of decision making and Business Intelligence to individuals or organizations. In this paper, we have performed an experimental study for different feature extraction or selection techniques available for opinion mining task. This experimental study is carried out in four stages. First, the data collection process has been done from readily available sources. Second, the pre-processing techniques are applied automatically using the tools to extract the terms, POS (Parts-of-Speech). Third, different feature selection or extraction techniq...

Monte-Carlo Tree Search For The "Mr Jack" Board Game A. Mazyad, F. Teytaud, And C. Fonlupt Univ Lille–Nord De France, France ABSTRACT Recently the use of the Monte-Carlo Tree Search algorithm, and in particular its most famous implementation, the Upper Confidence Tree can be seen has a key moment for artificial intelligence in games. This family of algorithms provides huge improvements in numerous games, such as Go, Havannah, Hex or Amazon. In this paper we study the use of this algorithm on the game of Mr Jack and in particular how to deal with a specific decision-making process.Mr Jack is a 2-player game, from the family of board games. We will present the difficulties of designing an artificial intelligence for this kind of games, and we show that Monte-Carlo Tree Search is robust enough to be competitive in this game with a smart approach. KEYWORDS Automatic Speech Recognition, MFCC, Zero crossing, Formants analysis, Autism Soft computing Original Source URL: http:...

Unsupervised learning models of invariant features in images: Recent developments in multistage architecture approach for object detection Sonia Mittal Nirma University, India ABSTRACT Object detection and recognition are important problems in computer vision and pattern recognition domain. Human beings are able to detect and classify objects effortlessly but replication of this ability on computer based systems has proved to be a non-trivial task. In particular, despite significant research efforts focused on meta- heuristic object detection and recognition, robust and reliable object recognition systems in real time remain elusive. Here we present a survey of one particular approach that has proved very promising for invariant feature recognition and which is a key initial stage of multi-stage network architecture methods for the high level task of object recognition KEYWORDS Unsupervised feature learning, CNNs, Tiled CNNs, Deep lear...

A Naive Method For Ontology Construction Preeti Kathiria and Sukraat Ahluwalia Nirma University, India ABSTRACT Ontologies are being used to organizeinformation in many domains like artificial intelligence,information science, semantic web, library science. Ontologies of an entity having different information can be merged to create more knowledge of that particular entity. Ontologies today are powering more accurate search and retrieval in websites like Wikipedia etc. As we move towards the future to Web 3.0,also termed as the semantic web, ontologies will play a more important role.Ontologies are represented in various forms like RDF, RDFS, XML, OWL etc. Querying ontologies can yield basic information about an entity. This paper proposes an automated method for ontology creation,using concepts from NLP (Natural Language Processing), Information Retrieval and Machine Learning.Concepts drawn from these domains help in designing more accurate ontologies represented using the XML fo...

Big Data Analytics: Challenges And Applications For Text, Audio, Video, And Social Media Data Jai Prakash Verma1, Smita Agrawal1, Bankim Patel2 and Atul Patel3 1Nirma University, India, 2UKA Trasadia University, India 3Charusat University,India ABSTRACT All types of machine automated systems are generating large amount of data in different forms like statistical, text, audio, video, sensor, and bio-metric data that emerges the term Big Data. In this paper we are discussing issues, challenges, and application of these types of Big Data with the consideration of big data dimensions. Here we are discussing social media data analytics, content based analytics, text data analytics, audio, and video data analytics their issues and expected application areas. It will motivate researchers to address these issues of storage, management, and retrieval of data known as Big Data. As well as the usages of Big Data analytics in India is also highlighted. KEYWORDS Big Data, Big Data Analytics,...

A Study on Graph Storage Database of NOSQL Smita Agrawal1 and Atul Patel Nirma University, India and 2Charusat University, India ABSTRACT Big Data is used to store huge volume of both structured and unstructured data which is so large and is hard to process using current / traditional database tools and software technologies. The goal of Big Data Storage Management is to ensure a high level of data quality and availability for business intellect and big data analytics applications. Graph database which is not most popular NoSQL database compare to relational database yet but it is a most powerful NoSQL database which can handle large volume of data in very efficient way. It is very difficult to manage large volume of data using traditional technology. Data retrieval time may be more as per database size gets increase. As solution of that NoSQL databases are available. This paper describe what is big data storage management, dimensions of big data, types of data, what is structured ...

ESTIMATION OF THE PARAMETERS OF SOLAR CELLS FROM CURRENT-VOLTAGE CHARACTERISTICS USING GENETIC ALGORITHM Suresh E. Puthanveettil1, Mengu Cho2and Amrita Suresh3 1ISRO Satellite Centre, Bangalore 560017, India 2Kyushu Institute of Technology, Kitakyushu, Japan Birla Institute of Technology and Science Pilani- K K Birla Campus,India ABSTRACT This paper presents a method for calculating the light generated current, the series resistance, shunt resistance and the two components of the reverse saturation current usually encountered in the double diode representation of the solar cell from the experimental values of the current-voltage characteristics of the cell using genetic algorithm. The theory is able to regenerate the above mentioned parameters to very good accuracy when applied to cell data that was generated from pre-defined parameters. The method is applied to various types of space quality solar cells and sub cells. All parameters except the light generated current are seen to ...

IMPLEMENTATION OF FOLKSONOMY BASED TAG CLOUD MODEL FOR INFORMATION RETRIEVAL FROM DOCUMENT REPOSITORY IN AN INDIAN UNIVERSITY Sohil D. Pandya1,Paresh V. Virparia2 and Rinku Chavda Sardar Vallabhbhai Patel Inst. of Technology (SVIT), Vasad, India ABSTRACT In the magnitude of internet one need to devote extra time to investigate anticipated resource, especially when one need to search information from documents. For the higher range internet there is serious need to demand the essentiality to discover the reserved resources. One of the solutions for information retrieval from document repository is to attach tags to documents. Numerous online social bookmarking services permit users to attach tags with resources which are eventually meta-data, frequently stated as folksonomy. In current paper, authors implemented this model for information retrieval by utilizing these tags, after retrieving by using delicious API and synthesize tag cloud in an Indian University to search and retrieve...