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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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IJARAI Vol. 2 Issue 5 (2013)

Open Access | | 11 papers

Copyright Statement: This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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1

Rice Crop Quality Evaluation Method through Regressive Analysis between Nitrogen Content and Near Infrared Reflectance of Rice Leaves Measured from Near Field

Author 1: Kohei Arai

Rice crop quality evaluation method through regressive analysis between nitrogen content in the rice leaves and near infrared reflectance measurement data from near field, from radio wave controlled helicopter is proposed. Rice quality dependency on nitrogen of chemical fertilizer and water supply condition is evaluated. Also homogeneity of the rice crop quality in the paddy fields is evaluated. Furthermore, influence due to shadow on near infrared reflectance of rice leaves measured from near field is taken into account in the rice crop quality evaluation processes.

rice crop regressive analysis nitrogen content reflectance measurement
Abstract doi.org/10.14569/IJARAI.2013.020501 PDF
2

Sea Ice Concentration Estimation Method with Satellite Based Visible to Near Infrared Radiometer Data Based on Category Decomposition

Author 1: Kohei Arai

Unmixing method for estimation of mixing ratio of the components of which the pixel in concern consists based on inversion theory is proposed together with its application to sea ice estimation method with satellite based visible to near infrared radiometer data. Through comparative study on the different unmixing methods with remote sensing satellite imagery data, it is found that the proposed inversion theory based unmixing method is superior to the other methods. Also it is found that the proposed unmixing method is applicable to sea ice concentration estimations.

Unmixing Inversion theory Category decomposition Remote Sensing
Abstract doi.org/10.14569/IJARAI.2013.020502 PDF
3

Sensitivity Analysis on Sea Surface Temperature Estimation Methods with Thermal Infrared Radiometer Data through Simulations

Author 1: Kohei Arai

Sensitivity analysis on Sea Surface Temperature: SST estimation with Thermal Infrared Radiometer: TIR data through simulations is conducted. Also Conjugate Gradient Method: CGM based SST estimation method is proposed. SST estimation error of the proposed CGM based method is compared to the conventional Split Window Method: SWM with a variety of conditions including atmospheric models. The results show that the proposed CGM based method is superior to the SWM.

SST estimation Split Window Conjugate Gradient MODTRAN atmospheric model
Abstract doi.org/10.14569/IJARAI.2013.020503 PDF
4

Image Clustering Method Based on Self Organization Mapping: SOM Derived Density Maps and Its Application for Landsat Thematic Mapper Image

Author 1: Kohei Arai

A new method for image clustering with density maps derived from Self-Organizing Maps (SOM) is proposed together with a clarification of learning processes during a construction of clusters. Simulation studies and the experiments with remote sensing satellite derived imagery data are conducted. It is found that the proposed SOM based image clustering method shows much better clustered result for both simulation and real satellite imagery data. It is also found that the separability among clusters of the proposed method is 16% longer than the existing k-mean clustering. It is also found that the separability among clusters of the proposed method is 16% longer than the existing k-mean clustering. In accordance with the experimental results with Landsat-5 TM image, it takes more than 20000 of iteration for convergence of the SOM learning processes.

SOM clustering Density map Boundary image Labeling algorithm
Abstract doi.org/10.14569/IJARAI.2013.020504 PDF
5

Remote Sensing Satellite Image Database System Allowing Image Portion Retrievals Utilizing Principal Component Which Consists Spectral and Spatial Features Extracted from Imagery Data

Author 1: Kohei Arai

Remote Sensing satellite image database which allows image portion retrievals utilizing principal component which consists of spectral and spatial features extracted from the imagery data is proposed. Through the experiments with actual remote sensing satellite images, it is found that the proposed image retrieval does work so well.

Image retrieval Spectral and spatial features e
Abstract doi.org/10.14569/IJARAI.2013.020505 PDF
6

Mashup Based Content Search Engine for Mobile Devices

Author 1: Kohei Arai

Mashup based content search engine for mobile devices is proposed. Example of the proposed search engine is implemented with Yahoo!JAPAN Web SearchAPI, Yahoo!JAPAN Image searchAPI, YouTube Data API, and Amazon Product Advertising API. The retrieved results are also merged and linked each other. Therefore, the different types of contents can be referred once an e-learning content is retrieved. The implemented search engine is evaluated with 20 students. The results show usefulness and effectiveness on e-learning content searches with a variety of content types, image, document, pdf files, moving picture.

search engine API mashup Andoride e-learning content retrieval
Abstract doi.org/10.14569/IJARAI.2013.020506 PDF
7

The preliminary results of a force feedback control for Sensorized Medical Robotics

Author 1: Duck Hee Lee Author 2: Seoung Joon Song Author 3: Reza Fazel-Rezai Author 4: Jaesoon Choi

A laparoscopic surgery system by using a robot holds many problems. Among these, its inability in delivering touching sensation to a surgeon is raised as the biggest problem. The current paper attempted to find a force feedback controlling method at the time of performing movement by using one-degree of freedom (DOF) arm of slave and master system that is used in the programming based system. The study was two methods experience force feedback control; In the first place used force sensors and otherwise, conducted for the force feedback control by using a force sensor and for the case when the sensor could not be used due to the spatial and systematic limitation. The realization of force feedback system was successful, and the experiment results of force feedback control and current based force feedback control mode based on the force sensors of one-DOF system indicates that it could be directly applied to the another multi-DOF surgical robot system that is currently under the development.

Laparoscopic surgery force feedback control degree of freedom (DOF).
Abstract doi.org/10.14569/IJARAI.2013.020507 PDF
8

Performance Analysis and Evaluation of Different Data Mining Algorithms used for Cancer Classification

Author 1: Gopala Krishna Murthy Nookala Author 2: Bharath Kumar Pottumuthu Author 3: Nagaraju Orsu Author 4: Suresh B. Mudunuri

Classification algorithms of data mining have been successfully applied in the recent years to predict cancer based on the gene expression data. Micro-array is a powerful diagnostic tool that can generate handful information of gene expression of all the human genes in a cell at once. Various classification algorithms can be applied on such micro-array data to devise methods that can predict the occurrence of tumor. However, the accuracy of such methods differ according to the classification algorithm used. Identifying the best classification algorithm among all available is a challenging task. In this study, we have made a comprehensive comparative analysis of 14 different classification algorithms and their performance has been evaluated by using 3 different cancer data sets. The results indicate that none of the classifiers outperformed all others in terms of the accuracy when applied on all the 3 data sets. Most of the algorithms performed better as the size of the data set is increased. We recommend the users not to stick to a particular classification method and should evaluate different classification algorithms and select the better algorithm.

Weka Cancer Classification Micro-array Data-mining Classification Algorithms Gene Expression Data
Abstract doi.org/10.14569/IJARAI.2013.020508 PDF
9

Path Based Mapping Technique for Robots

Author 1: Amiraj Dhawan Author 2: Parag Oak Author 3: Rahul Mishra Author 4: George Puthanpurackal

The purpose of this paper is to explore a new way of autonomous mapping. Current systems using perception techniques like LAZER or SONAR use probabilistic methods and have a drawback of allowing considerable uncertainty in the mapping process. Our approach is to break down the environment, specifically indoor, into reachable areas and objects, separated by boundaries, and identifying their shape, to render various navigable paths around them. This is a novel method to do away with uncertainties, as far as possible, at the cost of temporal efficiency. Also this system demands only minimum and cheap hardware, as it relies on only Infra-Red sensors to do the job.

Robots map generation navigation AI planning path planning
Abstract doi.org/10.14569/IJARAI.2013.020509 PDF
10

A New Optimization Algorithm For Combinatorial Problems

Author 1: Azmi Alazzam Author 2: Harold W. Lewis III

Combinatorial optimization problems are those problems that have a finite set of possible solutions. The best way to solve a combinatorial optimization problem is to check all the feasible solutions in the search space. However, checking all the feasible solutions is not always possible, especially when the search space is large. Thus, many meta-heuristic algorithms have been devised and modified to solve these problems. The meta-heuristic approaches are not guaranteed to find the optimal solution since they evaluate only a subset of the feasible solutions, but they try to explore different areas in the search space in a smart way to get a near-optimal solution in less cost and time. In this paper, we propose a new meta-heuristic algorithm that can be used for solving combinatorial optimization problems. The method introduced in this paper is named the Global Neighborhood Algorithm (GNA). The algorithm is principally based on a balance between both the global and local search. A set of random solutions are first generated from the global search space, and then the best solution will give the optimal value. After that, the algorithm will iterate, and in each iteration there will be two sets of generated solutions; one from the global search space and the other set of solutions will be generated from the neighborhood of the best solution. Throughout the paper, the algorithm will be delineated with examples. In the final phase of the research, the results of GNA will be discussed and compared with the results of Genetic Algorithm (GA) as an example of another optimization method.

meta-heuristic optimization combinatorial problems
Abstract doi.org/10.14569/IJARAI.2013.020510 PDF
11

Gesture Controlled Robot using Image Processing

Author 1: Harish Kumar Kaura Author 2: Vipul Honrao Author 3: Sayali Patil Author 4: Pravish Shetty

Service robots directly interact with people, so finding a more natural and easy user interface is of fundamental importance. While earlier works have focused primarily on issues such as manipulation and navigation in the environment, few robotic systems are used with user friendly interfaces that possess the ability to control the robot by natural means. To facilitate a feasible solution to this requirement, we have implemented a system through which the user can give commands to a wireless robot using gestures. Through this method, the user can control or navigate the robot by using gestures of his/her palm, thereby interacting with the robotic system. The command signals are generated from these gestures using image processing. These signals are then passed to the robot to navigate it in the specified directions.

Gestures OpenCV Arduino WiFly L293D.
Abstract doi.org/10.14569/IJARAI.2013.020511 PDF
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