IJARAI Volume 1 Issue 3

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Paper 1: Method for Learning Effciency Improvements Based on Gaze Location Notifications on e-learning Content Screen Display

Abstract: Method for learning efficiency improvement based on gaze notifications on e-learning content screen display is proposed. Experimental results with e-learning two types of contents (Relatively small motion of e-learning content and e-learning content with moving picture and annotation marks) show that 0.8038 to 0.9615 of R square value are observed between duration time period of proper gaze location and achievement test score.

Author 1: Kohei Arai

Keywords: Gaze estimation; e-learning content; thesaurus engine.

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Paper 2: Hybrid Metaheuristics for the Unrelated Parallel Machine Scheduling to Minimize Makespan and Maximum Just-in-Time Deviations

Abstract: This paper studies the unrelated parallel machine scheduling problem with three minimization objectives – makespan, maximum earliness, and maximum tardiness (MET-UPMSP). The last two objectives combined are related to just-in-time (JIT) performance of a solution. Three hybrid algorithms are presented to solve the MET-UPMSP: reactive GRASP with path relinking, dual-archived memetic algorithm (DAMA), and SPEA2. In order to improve the solution quality, min-max matching is included in the decoding scheme for each algorithm. An experiment is conducted to evaluate the performance of the three algorithms, using 100 (jobs) x 3 (machines) and 200 x 5 problem instances with three combinations of two due date factors – tight and range. The numerical results indicate that DAMA performs best and GRASP performs second for most problem instances in three performance metrics: HVR, GD, and Spread. The experimental results also show that incorporating min-max matching into decoding scheme significantly improves the solution quality for the two population-based algorithms. It is worth noting that the solutions produced by DAMA with matching decoding can be used as benchmark to evaluate the performance of other algorithms.

Author 1: Chiuh Cheng Chyu,
Author 2: Wei-Shung Chang

Keywords: Greedy randomized adaptive search procedure; memetic algorithms; multi-objective combinatorial optimization; unrelated parallel machine scheduling; min-max matching

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Paper 3: Fuzzy Controller Design Using FPGA for Photovoltaic Maximum Power Point Tracking

Abstract: The cell has optimum operating point to be able to get maximum power. To obtain Maximum Power from photovoltaic array, photovoltaic power system usually requires Maximum Power Point Tracking (MPPT) controller. This paper provides a small power photovoltaic control system based on fuzzy control with FPGA technology design and implementation for MPPT. The system composed of photovoltaic module, buck converter and the fuzzy logic controller implemented on FPGA for controlling on/off time of MOSFET switch of a buck converter. The proposed maximum power point tracking controller for photovoltaic system is tested using model designed by Matlab/Simulink program with graphical user interface (GUI) for entering the parameters of any array model using information from its datasheet, Simulation and experimental results show that performance of the fuzzy controller with FPGA in a maximum power tracking of a photovoltaic array can be made use of in several photovoltaic products and obtain satisfied result.

Author 1: Basil M Hamed
Author 2: Mohammed S. El-Moghany

Keywords: Fuzzy Control; MPPT; Photovoltaic System; FPGA.

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Paper 4: Automated Detection Method for Clustered Microcalcification in Mammogram Image Based on Statistical Textural Features

Abstract: Breast cancer is the most frightening cancer for women in the world. The current problem that closely related with this issue is how to deal with small calcification part inside the breast called micro calcification (MC). As a preventive way, a breast screening examination called mammogram is provided. Mammogram image with a considerable amount of MC has been a problem for the doctor and radiologist when they should determine correctly the region of interest, in this study is clustered MC. Therefore, we propose to develop an automated method to detect clustered MC utilizing two main methods, multi-branches standard deviation analysis for clustered MC detection and surrounding region dependence method for individual MC detection. Our proposed method was resulting in 70.8% of classification rate, then for the sensitivity and specificity obtained 79% and 87%, respectively. The gained results are adequately promising to be more developed in some areas.

Author 1: Kohei Arai
Author 2: Indra Nugraha Abdullah
Author 3: Hiroshi Okumura

Keywords: Automated Detection Method; Mammogram; Micro calcification; Statistical Textural Features; Standard Deviation.

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Paper 5: Temperature Control System Using Fuzzy Logic Technique

Abstract: Fuzzy logic technique is an innovative technology used in designing solutions for multi-parameter and non-linear control models for the definition of a control strategy. As a result, it delivers solutions faster than the conventional control design techniques. This paper thus presents a fuzzy logic based-temperature control system, which consists of a microcontroller, temperature sensor, and operational amplifier, Analogue to Digital Converter, display interface circuit and output interface circuit. It contains a design approach that uses fuzzy logic technique to achieve a controlled temperature output function.

Author 1: Isizoh A N
Author 2: Okide S.O
Author 3: Anazia A.E
Author 4: Ogu C.D

Keywords: Fuzzy logic; microcontroller; temperature sensor; Analogue to Digital Converter (ADC).

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Paper 6: A New Genetic Algorithm Based Lane-By-Pass Approach for Smooth Traffic Flow on Road Networks

Abstract: Traffic congestion in urban areas is a very critical problem and increasing day-by-day due to increment in number of vehicles and un-expandable traffic infrastructure. Several intelligent control systems have been developed to deal with this issue. In this paper, a new lane bypass algorithm has been developed for route diversion resulting in smooth traffic flow on the urban road networks. Genetic algorithms are utilized for the parameter optimization in this approach. Finally, the results of the proposed approach are found satisfactory.

Author 1: Shailendra Tahilyani,
Author 2: Manuj Darbari
Author 3: Praveen Kumar Shukla

Keywords: Genetic Algorithms, Fuzzy Logic, Neural Network, Activity Theory.

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Paper 7: Leaf Image Segmentation Based On the Combination of Wavelet Transform and K Means Clustering

Abstract: This paper focuses on Discrete Wavelet Transform (DWT) associated with the K means clustering for efficient plant leaf image segmentation. Segmentation is a basic pre-processing task in many image processing applications and essential to separate plant leafs from the background. Locating and segmenting plants from the background in an automated way is a common challenge in the analysis of plant images. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc.) in images. Image segmentation is a fundamental task in agriculture computer graphics vision. Although many methods are proposed, it is still difficult to accurately segment an arbitrary image by one particular method. In recent years, more and more attention has been paid to combine segmentation algorithms and information from multiple feature spaces (e.g. color, texture, and pattern) in order to improve segmentation results .The performance of the segmentation is analyzed by Jaccard, dice, variation of index and global consistency error method. The proposed approach is verified with real time plant leaf data base. The results of proposed approach gives better convergence when compare to existing segmentation method.

Author 1: N Valliammal
Author 2: Dr.S.N.Geethalakshmi

Keywords: Image segmentation; Wavelet Transform; Haar Wavelet; K means clustering algorithm.

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Paper 8: Poultry Diseases Warning System using Dempster-Shafer Theory and Web Mapping

Abstract: In this research, the researcher built a Web Mapping and Dempster-Shafer theory as an early warning system of poultry diseases. Early warning is the provision of timely and effective information, through identified institutions, that allows individuals exposed to a hazard to take action to avoid or reduce their risk and prepare for effective response. In this paper as an example we use five symptoms as major symptoms which include depression, combs, wattle, bluish face region, swollen face region, narrowness of eyes, and balance disorders. Research location is in the Lampung Province, South Sumatera. The researcher’s reason to choose Lampung Province in South Sumatera on the basis that has a high poultry population. Our approach uses Dempster-Shafer theory to combine beliefs in certain hypotheses under conditions of uncertainty and ignorance, and allows quantitative measurement of the belief and plausibility in our identification result. Web Mapping is also used for displaying maps on a screen to visualize the result of the identification process. The result reveal that Poultry Diseases Warning System has successfully identified the existence of poultry diseases and the maps can be displayed as the visualization.

Author 1: Andino Maseleno
Author 2: Md. Mahmud Hasan

Keywords: poultry diseases; early warning system; Dempster-Shafer theory, web mapping

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