Neuronemech Inc.

Philippines

Neuronemech Inc.

Philippines
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Hilado S.D.F.,De La Salle University - Manila | Gan Lim L.A.,De La Salle University - Manila | Naguib R.N.G.,Coventry University | Dadios E.P.,De La Salle University - Manila | And 3 more authors.
Journal of Advanced Computational Intelligence and Intelligent Informatics | Year: 2014

Colon cancer is one type of cancer that has a high death rate, but early diagnosis can improve the chances of patient recovery. Computer-assisted diagnosis can aid in determining whether images are of healthy or cancerous tissues. This study aims to contribute to the automatic classification of microscopic colonic images by implementing a 2-D wavelet transform for feature extraction and neural networks for classification. The colonic histopathological images are assigned to either the normal, cancerous, or adenomatous polyp classes. The proposed algorithm is able to determine which of the three classes the images belong to at a 91.11% rate of accuracy. © 2014, Fuji Technology Press. All rights reserved.


Vicerra R.R.P.,University of Santo Tomas of Philippines | Vicerra R.R.P.,De La Salle University - Manila | Dadios E.P.,De La Salle University - Manila | Dadios E.P.,Neuronemech Inc. | And 2 more authors.
Journal of Advanced Computational Intelligence and Intelligent Informatics | Year: 2014

This paper presents a swarm robot simulator for implementing underwater wireless communication network. Swarm intelligence is based on the collective behavior of social insects and animals such as ants, bees and others. In this paper, swarm was applied to overcome the challenges of transmitting data in a large underwater environment. A robot considered to be a member of the swarm acts as a simple "physical" carrier of the data, it moves until they converge and manage to form a link connecting the data transmitter and receiver. The system is developed, simulated and tested using a coded simulator. © 2014, Fuji Technology Press. All rights reserved.


Gustilo R.C.,De La Salle University - Manila | Dadios E.P.,De La Salle University - Manila | Dadios E.P.,Neuronemech Inc. | Calilung E.,De La Salle University - Manila | Gan Lim L.A.,De La Salle University - Manila
Journal of Advanced Computational Intelligence and Intelligent Informatics | Year: 2014

A small scale real time tiger prawn aquaculture setup was built and tested in the laboratory using ordinary aquariums to test the controllability and control of the four most important parameters in culturing tiger prawns, the temperature, salinity, pH and dissolved oxygen. These parameters were monitored using Vernier sensors via Labview program. The water quality index of the artificial habitat was monitored and computed using fuzzy logic. New values for the safe parameter conditions of the tiger prawns were observed and used in the computation of the water quality index. Lastly, electronic valves and actuators are used to automatically control the four said water parameters and set them to their optimal values. The control needed by each parameter to force them to stay within their optimal values was done using neural network. This control system is used to activate the electronic valves that will dispense correction fluids for each of the four monitored water parameter. © 2014, Fuji Technology Press. All rights reserved.


Gunay N.S.,Mindanao State University | Dadios E.P.,De La Salle University - Manila | Dadios E.P.,Neuronemech Inc. | Vicerra R.R.P.,University of Santo Tomas of Philippines | And 3 more authors.
Journal of Advanced Computational Intelligence and Intelligent Informatics | Year: 2014

This paper presents machine vision for locating and identifying 23 highly dynamic objects on 4.4 meters by 2.8 meters micro robot soccer playing field. The approach is based from the idea that the two camera vision subsystems should be synchronized and well informed in real time of the combined vision data and a selection of objects to track under each other's camera view. A measure of effectiveness on using incremental tracking for two-camera operation is developed and is used to evaluate the introduced approach through experimentation. A real-time visualization of the whole playfield containing the 22 micro robots and a golf ball is also provided for the system operator to validate the objects' actual poses with the vision system's measurements. Results show that the proposed technique is very fast, accurate, reliable, and robust to external disturbances. © 2014, Fuji Technology Press. All rights reserved.


Bandala A.A.,De La Salle University - Manila | Dadios E.P.,De La Salle University - Manila | Dadios E.P.,Neuronemech Inc. | Vicerra R.R.P.,University of Santo Tomas of Philippines | And 2 more authors.
Journal of Advanced Computational Intelligence and Intelligent Informatics | Year: 2014

This paper presents the fusion of swarm behavior in multi robotic system specifically the quadrotors unmanned aerial vehicle (QUAV) operations. This study directed on using robot swarms because of its key feature of decentralized processing amongst its member. This characteristic leads to advantages of robot operations because an individual robot failure will not affect the group performance. The algorithm emulating the animal or insect swarm behaviors is presented in this paper and implemented into an artificial robotic agent (QUAV) in computer simulations. The simulation results concluded that for increasing number of QUAV the aggregation accuracy increases with an accuracy of 90.62%. The experiment for foraging revealed that the number of QUAV does not affect the accuracy of the swarm instead the iterations needed are greatly improved with an average of 160.53 iterations from 50 to 500 QUAV. For swarm tracking, the average accuracy is 89.23%. The accuracy of the swarm formation is 84.65%. These results clearly defined that the swarm system is accurate enough to perform the tasks and robust in any QUAV number. © 2014, Fuji Technology Press. All rights reserved.

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