Author: Bioinformatics & Biosciences

Sundarapandian Vaidyanathan

ABSTRACT
This paper solves the output regulation problem of Sprott-I chaotic system, which is one of the classical chaotic systems discovered by J.C. Sprott (1994). Explicitly, for the constant tracking problem, new state feedback control laws have been derived for regulating the output of the Sprott-I chaotic system. Our controller design has been carried out using the regulator equations of C.I. Byrnes and A. Isidori (1990). The output regulation of the Sprott-I chaotic system has important applications in many areas of Science and Engineering. Numerical simulations are shown to illustrate the effectiveness of the control schemes proposed in this paper for the output regulation of the Sprott-I chaotic system.

KEYWORDS

Chaos; Feedback Control; Sprott-I System; Nonlinear Control Systems; Output Regulation.

For More details: https://wireilla.com/papers/ijbb/V2N2/2212ijbb03.pdf

Ashish Bhangale, Navneet Manjhi and Jyoti Bharti

ABSTRACT

The gait signature is extracted directly from the evidence gathering process. This is possible by using a Fourier series to describe the motion of the upper leg and apply temporal evidence gathering techniques to extract the moving model from a sequence of images. The improved classification capability of the phase-weighted magnitude information is verified using statistical analysis of the separation of clusters in the feature space. Furthermore, the technique is shown to be able to handle high levels of occlusion, which is of especial importance in gait as the human body is self-occluding. As such, a new technique has been developed to automatically extract and describe a moving articulated shape, the human leg, and shown its potential in gait as a biometric.

KEYWORDS

Fourier series, sequence of images, classification, phase-weighted magnitude, statistical analysis, occulation, articulated shape, biometric, VHT, HVHT, GAVHT, GA, SHT, CCD, FS & HHT

For More details: https://wireilla.com/papers/ijbb/V2N2/2212ijbb02.pdf

S. Qatawneh, A. Alneaimi, Th. Rawashdeh, M. Muhairat, R. Qahwaji and S. Ipson

ABSTRACT

DNA-binding proteins are a class of proteins which have a specific or general affinity to DNA and include three important components: transcription factors; nucleases, and histones. DNA-binding  proteins also perform important roles in many types of cellular activities. In this paper we describe machine learning systems for the prediction of DNA- binding proteins where a Support Vector Machine and a Cascade Correlation Neural Network are optimized and then compared to determine the learning algorithm that achieves the best prediction performance. The information used for classification is derived from characteristics that include overall charge, patch size and amino acids composition. In total 121 DNA- binding proteins and 238 non-binding proteins are used to build and evaluate the system. For SVM using the ANOVA Kernel with Jack-knife evaluation, an accuracy of 86.7% has been achieved with 91.1% for sensitivity and 85.3% for specificity. For CCNN optimized over the entire dataset with Jack knife evaluation we report an accuracy of 75.4%, while the values of specificity and sensitivity achieved
were 72.3% and 82.6%, respectively.

KEYWORDS

DNA-Binding Proteins, Machine Learning, SVM, CCNN, Jack-knife Technique

For more Details: https://wireilla.com/papers/ijbb/V2N2/2212ijbb01.pdf

S. M. Anzar and P. S. Sathidevi

ABSTRACT
The efficiency of a multibiometric system can be improved by weighting the scores obtained from the degraded modalities in an appropriate manner. In this paper, we propose an efficient PSO (Particle Swarm Optimization) based integration weight optimization scheme using d-prime statistics to determine the optimal weight factors for the complementary modalities, under different noise conditions. Instead of treating the weight estimation process from an algebraic point of view, an attempt is made to consider the same from the principles of linear programming techniques. The performance of the proposed method is analysed in the context of fingerprint and voice biometrics using sum rule of fusion. The d-prime statistics of fingerprint and voice modalities are measured and the integration weights are computed as the ratio of these two statistics. The computed d-prime ratio is then optimized against the recognition accuracy. The optimizing parameter is estimated in the training/validation phase using Leave-One-Out Cross Validation (LOOCV) technique. Experimental studies show that the proposed method improves recognition rate under normal operating conditions and reduces the FAR (False Acceptance Rate) considerably even at extreme low SNR (Signal to Noise Ratio) conditions. The proposed biometric solution can be easily integrated into any multibiometric system with score level fusion. Moreover, it finds extremely useful in applications where there are less number of available training samples.

KEYWORDS

Multibiometric System, Integration Weight, d-prime Statistics, Particle Swarm Optimization, Robustness

For More Details: https://wireilla.com/papers/ijbb/V2N3/2312ijbb04.pdf

Subhomoi Borkotoky

Abstract

HIV integrase is a 32 kDa protein produced from the C-terminal portion of the Pol gene product, and is an attractive target for new anti-HIV drugs. Integrase is an enzyme produced by a retrovirus (such as HIV) that enables its genetic material to be integrated into the DNA of the infected cell. Raltegravir and Elvitegravir are two important drugs against integrase.

Keywords

Integrase, Chemsketch, Virtual screening.

For more Details: https://wireilla.com/papers/ijbb/V2N3/2312ijbb03.pdf

Srinivas Koppu, V. Madhu Viswanatham and Kamalakannan

ABSTRACT

This paper identifies the different kinds of methods, which helps human to communicate with computer. Traditionally the user interacting with computer via command line or GUI or common hand-held devices such as mouse and keyboard which is not feasible for a handicapped or a blind or a mute people. In order to interact with computer, the good interface required, the interface is sub part of human computer Interaction (HCI). HCI not only software design, it also concentrates on design of hardware devices. Describe the interaction between Brain and Computer based on EEG patterns. Brain generates EEG signal Based upon that system has to act and it has to perform tasks like human in real world. Thus the research work that is proposed would be to build a human to computer interaction through EEG signal. The system that allow the user to interact directly brain to computer based EEG signal and no need to use any input device to interact with any type of systems such are computer , TV’s. This way the computer
system can reduce the man work needed to feed information into the system by a large extent.

KEYWORDS

EEG signal, Brain Computer Interface (BCI), Human Computer Interaction (HCI), Speech Recognizer, Neural Networks, Cognitive Science.

For More Details: https://wireilla.com/papers/ijbb/V2N3/2312ijbb02.pdf

Guillaume Koum¹ and Josiane Etang

Abstract

A geo-ontology can be built around a Geographic Information System (GIS) and enriched with a firstorder logic language under the closed-world assumption (CWA). This extended system provides knowledge representation formalisms that are aimed to describe general conceptual information. They can also be used in the construction of the knowledge base of a reasoning tool. In this paper an environment is defined where a geo-ontology offers possibilities with a system that allows users to represent and reason about some aspects of the real world. With respect to the added intelligence; knowledge is preserved and enhanced. Knowledge enhancement is performed under the CWA in a subset of the first-order logic language. A geo-reasoning task is undertaken so that a GIS and a geo-ontology are integrated in what can correspond to a natural language processing system. The framework is implemented to demonstrate geo-ontology’s ability to enhance knowledge in malaria control domain.

Keywords

geographic information system, geo-ontology; closed-world assumption, geo-reasoning, malaria control

For more details: https://wireilla.com/papers/ijbb/V2N3/2312ijbb01.pdf

Shashank Rana, Shrikant Sharma and Raghvendar Singh

Abstract
Lactoferrin is an iron binding globular protein with antimicrobial activity was firstly isolated in bovine milk. Lactoferrin (LF) is structurally similar to the transferrins. So it is also known as lactotransferrin (LTF) is a globular multifunctional protein. Our work was on motif discovery by using OOPS modal of MEME (Multiple EM for Motif Elicitation) tool. The aim of motif discovery is to detect short, highly conserved patterns in a collection of unaligned DNA or protein sequences. We have taken fifteen LTF AA sequencesfrom different resources.By analysis of these sequences, three motifs were retrieved. It is to be noted that all fifteen sequences contains all three motifs but start points of those are different. Each motif has 15 sites and 50 widths. On the bases of motif analysis, it is distinct that LTF retrieved from any milk recourse, have common conserved patterns.

Keywords

MEME, LTF, OOPS, Conserved pattern, MAST

For More Details: https://wireilla.com/papers/ijbb/V2N4/2412ijbb03.pdf

Hossein Jadidoleslamy

ABSTRACT
People authentication based on fingerprint is one of the most important people authentication techniques which it used biology specifications. The main purpose of this paper is discussing on minutiae-based extraction methods for fingerprints comparison and presenting a new pattern matching algorithm in this area; of course, this algorithm also has been presented based on comparing fingerprint features (especially minutiae points).

KEYWORDS

Biometric, Fingerprint, Minutiae, Automated Fingerprint Identification System (AFIS), Extraction, Matching

For More Details: https://wireilla.com/papers/ijbb/V2N4/2412ijbb02.pdf

João Fradinho Oliveira, Hugo Capote, José Blas Pagador, José Luis Moyano, Cuevas, Francisco Miguel Sánchez Margallo

ABSTRACT
Minimally invasive surgery has become a widely used surgical technique that improves patients’ safety and optimizes health resources. Specifically, laparoscopic surgery uses small incisions through the abdomen to operate, for example a liver, with minimal postoperative complications and faster recoveries. However, the cognitive load and surgical skills required by surgeons increase when compared to open surgery. For these reasons, specific training models and new technologies are needed to assist surgeons. One of this kind of systems are Computer Assisted Surgery systems that enable the display of computer generated imagery of pre- and intra-operative data to assist surgeons during its surgical procedures, but in many hospitals either they are not used at a basic level due to socio-economic challenges or components still face considerable technical challenges that must be solved. In this paper we list some of the difficulties that CAS components face during a laparoscopic surgery and highlight the benefits that a new job profile, the computer assisted surgery system nurse could bring in several modelling and tracking scenarios.

KEYWORDS

Laparoscopic surgery, 3D reconstruction, navigation, tracking, computer assisted surgery system nurse

For More Details: https://wireilla.com/papers/ijbb/V2N4/2412ijbb01.pdf