IJARAI Volume 5 Issue 1

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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Paper 1: Comparative Study of Optimization Methods for Estimation of Sea Surface Temperature and Ocean Wind with Microwave Radiometer Data

Abstract: Comparative study of optimization methods for estimation sea surface temperature and ocean wind with microwave radiometer data is conducted. The well known mesh method (Grid Search Method: GSM), regressive method, and simulated annealing method are compared. Surface emissivity is estimated with the simulated annealing and compared to the well known Thomas T. Wilheit model based emissivity. On the other hand, brightness temperature of microwave radiometer as a function of observation angle is estimated by the simulated annealing method and compares it to the actual microwave radiometer data. Also, simultaneous estimation of sea surface temperature and ocean wind speed is carried out by the simulated annealing and compared it to the estimated those by the GSM method. The experimental results show the simulated annealing which allows estimation of global optimum is superior to the other method in some extent.

Author 1: Kohei Arai

Keywords: Microwave radiometer; remote sensing; sea surface temperature; nonlinear optimization theory; simulated annealing

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Paper 2: Rescue System with Health Condition Monitoring Together with Location and Attitude Monitoring as Well as the Other Data Acquired with Mobile Devices

Abstract: Rescue system with health condition monitoring together with location and attitude monitoring as well as the other data acquired with mobile devices is proposed. Backup system for location estimation is also proposed. On behalf of GPS receivers and WiFi beacon receivers, ZigBee is used as a backup system. Attitude can be monitored with acceleration-meters equipped in the commercially available smart phones and i-phones. Also, the number of steps and calorie consumptions can be monitored with the commercially available smart phones and i-phones. By using these body attached sensors, health condition of the persons who need a help for rescue when the emergency situations can be monitored and used for rescue planning and triage. Overall system configuration is proposed together with the detailed system descriptions with some of the experimental data.

Author 1: Kohei Arai
Author 2: Taka Eguchi

Keywords: Rescue system; Location estimation; Attitude estimation; Health monitoring; Mobile applications; Triage; Rescue planning

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Paper 3: Evaluation of Cirrus Cloud Detection Accuracy of GOSAT/CAI and Landsat-8 with Laser Radar: Lidar and Confirmation with Calipso Data

Abstract: Cirrus cloud detection accuracy of GOSAT/CAI and Landsat-8 is evaluated with a ground based Laser Radar: Lidar data and sky view camera data. Also, the evaluation results are confirmed with Calipso data together with a topographic representation of vertical profile of cloud structure. Furthermore, origin of cirrus clouds is estimated with forward trajectory analysis. The results show that GOSAT/CAI de4rived cirrus clouds is not accurately enough due to missing of cirrus cloud detection spectral channel while Landsat-8 derived cirrus cloud.

Author 1: Kohei Arai
Author 2: Masanori Sakashita

Keywords: Cirrus cloud; GOSAT/CAI; Landsat; LiDAR; Sky view camera; Calipso; topogramphic representation of 3D clouds

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Paper 4: An Empirical Comparison of Tree-Based Learning Algorithms: An Egyptian Rice Diseases Classification Case Study

Abstract: Applications of learning algorithms in knowledge discovery are promising and relevant area of research. The classification algorithms of data mining have been successfully applied in the recent years to predict Egyptian rice diseases. Various classification algorithms can be applied on such data to devise methods that can predict the occurrence of diseases. However, the accuracy of such techniques differ according to the learning and classification rule used. Identifying the best classification algorithm among all available is a challenging task. In this study, a comprehensive comparative analysis of a tree-based different classification algorithms and their performance has been evaluated by using Egyptian rice diseases data set. The experimental results demonstrate that the performance of each classifier and the results indicate that the decision tree gave the best results.

Author 1: Mohammed E. El-Telbany
Author 2: Mahmoud Warda

Keywords: Data Mining, Classification, Decision Trees, Bayesian Network, Random Forest, Rice Diseases.

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Paper 5: Bidirectional Extraction of Phrases for Expanding Queries in Academic Paper Retrieval

Abstract: This paper proposes a new method for query expansion based on bidirectional extraction of phrases as word n-grams from research paper titles. The proposed method aims to extract information relevant to users’ needs and interests and thus to provide a useful system for technical paper retrieval. The outcome of proposed method are the trigrams as phrases that can be used for query expansion. First, word trigrams are extracted from research paper titles. Second, a co-occurrence graph of the extracted trigrams is constructed. To construct the co-occurrence graph, the direction of edges is considered in two ways: forward and reverse. In the forward and reverse co-occurrence graphs, the trigrams point to other trigrams appearing after and before them in a paper title, respectively. Third, Jaccard similarity is computed between trigrams as the weight of the graph edge. Fourth, the weighted version of PageRank is applied. Consequently, the following two types of phrases can be obtained as the trigrams associated with the higher PageRank scores. The trigrams of the one type, which are obtained from the forward co-occurrence graph, can form a more specific query when users add a technical word or words before them. Those of the other type, obtained from the reverse co-occurrence graph, can form a more specific query when users add a technical word or words after them. The extraction of phrases is evaluated as additional features in the paper title classification task using SVM. The experimental results show that the classification accuracy is improved than the accuracy achieved when the standard TF-IDF text features are only used. Moreover, the trigrams extracted by the proposed method can be utilized to expand query words in research paper retrieval.

Author 1: Yuzana Win
Author 2: Tomonari Masada

Keywords: word n-grams; Jaccard similarity; PageRank; TF-IDF; query expansion; information retrieval; feature extraction

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