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Time-Based Raga Recommendation and Information Retrieval of Musical Patterns in Indian Classical Music Using Neural Networks Samarjit Roy; Sudipta Chakrabarty; Debashis De
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 6, No 1: March 2017
Publisher : Institute of Advanced Engineering and Science

In Indian Classical Music (ICM) perspective, Raga is formed from the different and correct combination of notes. If it is observed the history of Indian Classical Raga in ICM, the playing or serving each of the ragas has some unique sessions. The procedure is to suggest the classifications of playing a raga has been attempted to display by explaining unique musical features and pattern matching. This contribution has been represented how music structures can be advanced through a more conceptual demonstration and consent to unambiguously describe process of computational modeling of Musicology which signify the challenge on complete musical composition from the elementary vocal objects of ICM usage using Neural Networks. In Neural network the samples of various ragas have been taken as input and classify them according to the times of the performance. Over 90% accuracy level has achieved using entire Confusion Matrices and Error Histogram performance evaluation technique.

Building Information Modelling Penetration Factors in Malaysia W. I. Enegbuma; Y. A. Dodo; K. N. Ali
International Journal of Advances in Applied Sciences Vol 3, No 1: March 2014
Publisher : Institute of Advanced Engineering and Science

The construction industry master plan in Malaysia provides ample leverage towards information technology improvements in the construction industry. Building Information Modelling (BIM) transforms the means to which the traditionally thought method is construction is carried out. Changes occur in aspects of people, process and technology during such transformation. Information technology (IT) acceptance theories of Theory of Reasoned Action (TRA), Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB), Innovation Diffusion Theory (IDT), Decomposed Theory of Planned Behaviour (DTPB), Extension of Technology Acceptance Model (TAM2) and Unified Theory of Acceptance and Use of Technology stipulates underlining theories to accessing user perception to new systems such as BIM. This paper presents the linking paths to factors of user perceptions (people, process and technology) and how they react in strategic IT implementation and collaborative environment to fully support extensive BIM penetration in the industry. The study further extends the BIM penetration model by Enegbuma and Ali (2012). The model will aid industry practitioners to tackle the various challenges experienced with BIM implementation. Future research will focus on solidifying the proposal with data analysis.

Intelligent Information System for Suspicious Human Activity Detection in Day and Night J L Mazher Iqbal; S. Arun
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 7, No 3: December 2018
Publisher : Institute of Advanced Engineering and Science

The detection of human beings in a camera attracts more attention because of its wide range of applications such as abnormal event detection, person counting in a dense crowd, person identification, fall detection for care to elderly people, etc. Over the time, various techniques have evolved to enhance the visual information. This article presents a novel 3-D intelligent information system for identifying abnormal human activity using background subtraction, rectification, morphology, neural networks and depth estimation with a thermal camera and a pair of hand held Universal Serial Bus (USB) camera to visualize un-calibrated images. The proposed system detects strongest points using Speed-Up Robust Features (SURF). The Sum of Absolute Difference (SAD) algorithm match the strongest points detected by SURF. 3-D object model and image stitching from image sequences are carried out in the proposed work. A series of images captured from different cameras are stitched into a geometrically consistent mosaic either horizontally/vertically based on the image acquisition. 3-D image and depth estimation of un-calibrated stereo images are acquired using rectification and disparity. The background is separated from the scene using threshold approach. Features are extracted using morphological operators in order to get the skeleton. Junction points and end points of the skeleton image are obtained from the skeleton. Data set of abnormal human activity is created using supervised learning such as neural network with a thermal camera and a pair of webcam. The feature vector of an activity is compared with already created data set, if a match occurs the classifier detects abnormal human activity. Additionally the proposed algorithm performs depth estimation to measure real time distance of objects dynamically. The system use thermal camera, Intel computing stick, converter, video graphics array (VGA) to high-definition multimedia interface (HDMI) and webcams. The proposed novel intelligent information system gives 94% maximum accuracy and 89% minimum accuracy for different activities, thus it effectively detects suspicious activity during day and night.

An Efficient System for Information Recommendation Zhenhua Huang; Qiang Fang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 6: June 2014
Publisher : Institute of Advanced Engineering and Science

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A recommendation system is the one of the most effective tools for tackling with the problem of information overload. However, as the maturity of Web 2.0 and the emergence of massive information, the existing information recommendation systems have the serious drawbacks in the aspects of real-timing, robustness and self-adaptability. Motivated by the above facts, in this paper, we design SIRSCA, which is an efficient semantic-driven information recommendation system under the cloud architecture. Specially, the SIRSCA system mainly include four modules: semantics representation of foundation data and user preference informations; indexing mechanism of massive semantic informations under cloud architecture; recommendation approaches based on semantic computation theory; and technologies of dynamic migration under cloud architecture. We present the extensive experiments that demonstrate our improved system is both efficient and effective. DOI: http://dx.doi.org/10.11591/telkomnika.v12i6.5445

Fuzzy Information Modeling in a Database System Salam Ismaeel; Ayman Al-Khazraji; Karama Al-delimi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 6, No 1: March 2017
Publisher : Institute of Advanced Engineering and Science

A Fuzzy logic (FL) provides a remarkably simple way to draw definite conclusions from vague, ambiguous or imprecise information. In a sense, fuzzy logic resembles human decision making with its ability to work from approximate data and find precise solutions. In this paper a fuzzy information modeling system was developed then used in a database, which contains fuzzy data and real data, to create new information assistance capable of making any decision about this data. The proposed system is implemented on a special database used to evaluation workers or users in any formal organizations.

Gamified Android-Based Academic Information System Henry Setiana; Seng Hansun
International Journal of Evaluation and Research in Education (IJERE) Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

Student is often lazy when it comes to studying, and how to motivate student was one of the problem in the educational world. To overcome the matters, we will implement the gamification method into an Academic Information System. Academic Information System is a software used for providing information and arranging administration which connected with academic activities. By implementing the gamification method, it is expected to improve student’s interest on the study programs. Gamification itself is a process with the purpose of changing non-game context into a more interesting application by integrating game thinking, game design, and game mechanics. From the evaluation result, it is concluded that the application has been successfully built and the gamification method has been successfully implemented to improve student’s interest and the most influential gamification features are point and reward.

Web-based Geographic Information System Design of Rabies Spread in Bali I. A. K. Sita Laksmita; A. A. Kompiang Oka Sudana; Putu Wira Buana
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 1, No 1: June 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (719.511 KB)

Rabies is still a serious threat in the province of Bali. Because of that Bali need a good management system service that can process data and information to support the government to make decision for preventing rabies outbreak. Nowadays, data management still uses spreadsheet technology that oriented to attribute data. Geographic Information System (GIS) is a system that has the ability to process, analysis the process and analyzes spatial data or data with geographic coordinates. This article will discuss the implementation of GIS that show the spread of rabies in the province of Bali by using GeoServer as the Open Geospatial Consortium (OGC) standards-compliant server to provide geospatial data via web services. These GIS application, supported by PostGIS database as storage and processing of spatial data and OpenLayers as an interface. This application can support government for making priority decision to focus on areas which has the most high of rabies outbreak.DOI: http://dx.doi.org/10.11591/ij-ict.v1i1.589

On the High Dimentional Information Processing in Quaternionic Domain and its Applications Sushil Kumar; Bipin Kumar Tripathi
International Journal of Advances in Applied Sciences Vol 7, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

There are various high dimensional engineering and scientific applications in communication, control, robotics, computer vision, biometrics, etc.; where researchers are facing problem to design an intelligent and robust neural system which can process higher dimensional information efficiently. The conventional real-valued neural networks are tried to solve the problem associated with high dimensional parameters, but the required network structure possesses high complexity and are very time consuming and weak to noise. These networks are also not able to learn magnitude and phase values simultaneously in space. The quaternion is the number, which possesses the magnitude in all four directions and phase information is embedded within it. This paper presents a well generalized learning machine with a quaternionic domain neural network that can finely process magnitude and phase information of high dimension data without any hassle. The learning and generalization capability of the proposed learning machine is presented through a wide spectrum of simulations which demonstrate the significance of the work.

Rough Set Extension Model of Incomplete Information System Yue Hou
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 4: April 2014
Publisher : Institute of Advanced Engineering and Science

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This paper investigated the incomplete information system in which situation of the more missing or absent unknown values. Based on the original characteristic relation, we proposed a new reflective relation which was controlled by the parameter alpha, beta. By analyzing illustrative examples and comparing to the original characteristic relation, this paper indicated the validity and practicability of the new-defined binary relation. DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4732

Spatial Information based Image Clustering with A Swarm Approach Ouadfel Salima; Abdelmalik Taleb-Ahmed; Batouche Mohamed
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 1, No 3: September 2012
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (290.249 KB)

Fuzzy c-means algorithm (FCM) is one of the most used clustering methods for image segmentation. However, the conventional FCM algorithm presents some limits like its sensitivity to the noise because it does not take into consideration contextual information and its convergence to local minimum since it is based on a gradient descent method. In this paper, we present a new spatial fuzzy clustering algorithm optimized by the Artificial Bee Colony (ABC) algorithm. ABC-SFCM has two major characteristics. First it tackles better noisy image segmentation by making use of the spatial local information into the membership function. Secondly, it improves the global performance by taking advantages of the global search capability of ABC. Experiments with synthetic and real images show that ABC-SFCM is robust to noise compared to other methods.DOI: http://dx.doi.org/10.11591/ij-ai.v1i3.765

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