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Showing 145–156 of 180 results
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A Novel Recognition System for Digits Writing in the Air Using Coordinated Path Ordering
Open AccessAbstract: With the invention of Microsoft Kinect sensor, human-computer interaction is gaining its
attention and becoming available for widespread use. The previous study presented a method of
Kinect-based mid-air handwritten digit recognition for Android smart phones with a recognition
accuracy of only about 94.6%. In this paper, we propose an improved method based on the
normalizing and scaling of path order coordinates. With that, the proposed method leads to accuracy elevation and executing time reduction. Experimental results show an average recognition accuracy rate of 96.8% was achieved for each number.
Keywords: Accuracy rate, handwritten digit recognition, human-computer interaction, Kinect sensor support vector machine -
Path Detection in Virtual Environment for Synchronous EEG by Density Based Support Vector Machine
Open AccessAbstract: The use of Brain-Computer Interface (BCI) has been increasing exponentially in the recent years due to the use of low-cost commercial Fast Fourier Transform (FFT) based EEG reading devices with nonclinical accuracy for consumer application development. Also, the design and implementation of 3D virtual environments for BCI training purposes has proven to be effective due to the high interaction with the end user and the assistance for recreating a specific type of signal or behavior. The aim of this paper is to present a method and the results of applying a binary Density Based Support Vector Machine (DBSVM) Classifier in a 3D virtual environment designed for interaction with EEG predefined signal patterns. The environment trains the classifier by taking 180 second EPOCHs and classifying them into a successful/unsuccessful attempt per test subject. The applications can be extended for implementing mind-wave pattern password or tracing a specific set of mind-based commands for virtual path tracing purposes. The tested SVM had a success rate of 60%. Further work includes the study of different classifier features and implementation of a dynamic classifier.
Keywords: BMI, MindWave, SVM, Pattern Recognition, Machine Learning -
Electrical impedance imaging based on ultrasonic B-mode image
Open AccessAbstract: This paper presents electrical impedance imaging based on ultrasonic B-mode image for
detecting breast tumor. In the proposed system, a thin film with 16 electrodes was pasted on the
surface of the ultrasound probe. The proposed system allows both the electrical conductivity image by sixteen film electrodes and ultrasound image by the ultrasonic probe at same area. The electrical conductivity image is improved by using ultrasound image as the prior information. In the simulation and experiment, the electrical conductivity distribution at the simple breast model was reconstructed by the proposed system. The comparison between the electrical images with and without the ultrasound image as the prior information was presented. As results, it was found that the electrical conductivity distribution was clearly improved by using ultrasonic image as the prior information although the proposed system must be improved.
Keywords: Ultrasonic imaging, electrical impedance imaging, linear array sensor -
Construction of Hydraulically Balanced Water Distribution Network
Open AccessAbstract: This paper represents creating and analyzing of an adequate hydraulically balanced Water Distribution Network (WDN) based on Geographical Information System (GIS) and Epanet softwares. Fist a proper and functional WDN has been built and skeletonized by network analyst methodology in ArcGIS. Then the project scenario has been imported into Epanet with simple text or Epanet’s readable format consisted of multiple physical or non-physical WDN objects and its characteristics. These all in order to determine analyze and simulate hydraulic parameters of WDN. Second, we analyzed and determined water flows, water in each pipe, water flows direction as well as pressure heads at each node in the network with other required hydraulics parameters. The advantages of this method are simple math and self-correction.
Concisely, the context of this work is to use GIS and Epanet-based methodologies as well as
solution of closed-loop network problems. Used continuity and energy conservation methods due to determination of pressure heads at each node, water flows and water flows direction at each pipe in the network. As a result got a satisfied hydraulically balanced and a systematic WDN appropriately as the implications of this paper approaches consequently.
Keywords: Geographical Information System (GIS); Water Distribution Network (WDN), Hydraulic,
Epanet. -
Homotopic parts configuration management using the cellular data system
Open AccessAbstract: Lacking proper theory and design, big data has continued to grow in a chaotic way and are now beyond human recognition and control. To address this, we have been researching an application of the concept of homotopy preservation in homotopy type theory to remove the bottleneck in big data processing, originating from combinatorial explosion of information, which makes use of the seven layers, from homotopy to presentation, of the incrementally modular abstraction hierarchy (IMAH).
We developed the Cellular Data System (CDS) as an implementation of the IMAH in our previous
work. In this paper, we introduce a position information formula, which identifies the relative position of a specified factor in a formula in CDS. This function has an important role for preserving homotopy in actual changes of objects. We show the effectiveness of the formula by taking up a case study of component configuration information management in manufacturing. In the case study, it is demonstrated that design component configuration information and manufacturing component configuration information are consistently managed by preserving homotopy, even when component configuration frequently changes.
Keywords: Position information formula, Component configuration information management,
Incrementally Modular Abstraction Hierarchy, Cellular Data System -
An Analysis Of Automated HTML5 Offline Services (AHOS)
Open AccessAbstract: The classic web-based applications operate only when connected to the network. Many
realities in a field require a web-based application that is applicable even in case of offline. We have proposed the Automated HTML5 Offline Service (AHOS), presented as the integration of advanced services, developing with HTML5 Application Programming Interfaces (APIs) to provide web-based applications with the ability to work offline. When the AHOS web-based application visits at the web server for the first time, the web server will notify the application the list of files required to be downloaded. Then after being downloaded, the web application can work successfully and continuously even though the network connection from the client to the server is unavailable. Moreover, if the connection to the server is re-connected, any changes that have been made during offline will be automatically uploaded. The present study describes the requirements and implementation stages of AHOS concept for web-based applications. Then, several current status and challenges of AHOS concept are also described. The performance analyses of the AHOS concept are performed in a case of web-based maintenance Decision Support System (DSS) for Small and Medium Industries (SMIs). The results of the study are very useful in providing in-depth understanding of the advantages and limitations, and as the future directions in applying this AHOS concept to other webbased applications.
Keywords: Hypertext markup language fifth revision, Offline services, Synchronization service, Webbased applications. -
The Impact of Trait Anxiety under a Painful Stimulus on the Chaotic Synchronization of Respiration and Pulse Waves
Open AccessAbstract: Thus far, attention has been paid to the relation between pain and anxiety, which has been studied. On the other hands, the earlier studies have hinted at the importance of considering mental and physical health from a holistic perspective, while taking into consideration the principles that prescribe the chaotic behavior of living organisms. Therefore, the purpose of this study is to use the respiration and pulse waves to examine the nature of the chaotic connection between biosignals involved in people’s mental and physical conditions, particularly those involved in the psychological trait of anxiety under a painful stimulus in this case. The results showed that with the high anxiety group, the extent of the synchronicity between their respiration and pulse waves under a painful stimulus increased, while this decreased for the low anxiety group. In other words, chaos dynamics for living systems are expressed in synchronous phenomena for the LLE for respiration and pulse waves. It also implied that these dynamics are prescribed by trait anxiety under a painful stimulus. This has opened up the possibility that, in the future, the cross-correlation function for LLE in pulse waves and respiration will make contributions to treating and assessing chronic pain in the field of clinical medicine.
Keywords: Pain; Anxiety; Chaos; Synchronization -
JBINS Vol 2 Issue 2
Open AccessPublished 26th April 2016, ISSN 2188-8116, Total Pages 9
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Processing of retinal signals in the Limulus brain
Open AccessAbstract: Limulus retina sends signals to the brain through optic nerve fibers with processes terminating in both the first and second optic ganglia, called lamina and medulla. At the lamina, OFF signals are generated and sent to the medulla. Medullar cells extend fibers to the other parts of the brain. To understand the neural mechanisms of their visually guided mating behavior, it is important to investigate responses in the medulla. However, there are only very few studies on medulla due to experimental difficulties. In this paper, we developed two experimental setups to study the medulla ex vivo and succeeded in recording responses and in mapping receptive fields. Responses of medullar cells share many features with responses of ganglion cells in vertebrate retina. The recorded responses can be classified as non-spiking, sustained and transient ON, sustained and transient OFF, ON-OFF, inhibition, and bilateral and contralateral types. Their receptive fields vary from 6 degrees to more than 180 degrees. Some cells have receptive fields classified as ON-center and OFF-center. In addition, one medullar cell had a separated receptive field extending over 90 degrees in the horizontal direction.
Keywords: visual processing, intracellular recording, medulla, brain, invertebrate, Limulus
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JBINS Vol. 1 Issue 1
Open AccessPublication Date: 25th December 2015, ISSN 2188-8116, Total Pages 61
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Multi-Color Recognition based on Mini-Max Color Threshold for Medical Purpose
Open AccessAbstract: This paper discusses the multi-color recognition using the min-max color threshold for
outdoor robot navigation. All colors used in this project are RGB orthogonal color space in order to
see how much of each primary color between min and max that can be observed in the color to be
recognized. The white color value in the color space is set as the object for which the target color to be recognized belongs, while the black color value is set as the object background. The recognition process is done by summing up first the values of the red, green and blue in each color to obtain the rgb sum value, which is then divided by the individual color element to obtain the color threshold. This threshold is compared to the originally color threshold for the recognition, where a satisfactory result is expected as the project is not yet finished.
Keywords: Color recognition, threshold, mini-max, multicolor -
Comparing Two Feature Selection Methods for Influenza-A Antivral Resistance Determination
Open AccessAbstract: The paper thoroughly analyzes the use of Principal Component Analysis (PCA) in
comparison to Information Gain (IG) as a feature selection method for improving the classification of Influenza-A antiviral resistance. Neural networks were used as the classification method of choice with PCA, while decision trees were the classification of choice with IG. The experiment was conducted on cDNA viral segments of Influenza-A belonging to the H1N1 strain. The 7 Infleunza-A segments generating the best results were used for comparison. Sequences from each segment were further divided into Adamantane-resistant, & non-Adamantane-resistant. Accuracy, sensitivity, specificity precision & time were used as performance measures. Using PCA for feature selection increased preprocessing speeds from an average processing time of 1.5 hours to 5 minutes, as opposed to IG. IG had higher accuracy. The best accuracy generated by PCA & NNs on the M1/M2 was 96.5%, while that of IG & DTs was 98.2% Using PCA features & DTs also generated a comparable accuracy to that of IG features & DT at 97.6% on the M1/M2 segment. There was a 88% increase in feature selection processing speed when using PCA compared to IG on the M1/M2 segment alone.
Keywords: Influenza-A, Principle component analysis (PCA), Machine learning, Information gain,
DNA classification, decision trees, neural networks.